In this paper, an idea for improvement of suffix array construction using lazy evaluation is presented. Evaluation of the suffix array is based on the searching queries; only the necessary part of the suffix array is built when unevaluated part of the suffix array is referred during the searching process. This is less time consuming than constructing complete suffix array. We propose lazy evaluation of Schürmann-Stoye algorithm. Experimental results show that lazy Schürmann-Stoye algorithm runs faster than Maniscalco, which is well-recognized as the fastest suffix sorting algorithm, under the constraint of small LCP (longest common prefix) and a limited number of searching queries.

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Multi-source broadcasting is one of the information dissemination problems on communication networks such that some units disseminate distinct messages to all other units. In this paper, we study multi-source broadcasting on the de Bruijn and Kautz digraphs which are the models of interconnection networks. In [8] and [12], a cycle-rooted tree which has a large root-cycle is constructed by composition of isomorphic factors, and the multi-source broadcasting is executed on the cycle-rooted tree. On the other side, we execute multi-source broadcasting on each isomorphic factors at the same time. We present a method for multi-source broadcasting using isomorphic cycle-rooted trees which factorize these digraphs, and investigate its efficiency.

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In this paper, we consider a problem of assigning n independent tasks onto m identical processors in such a way that the overall execution time of the tasks will be minimized. Unlike conventional task assignment problem, we assume that the execution time of each task is not fixed in advance, and merely upper and lower bounds of the execution time are given at the compile time. In the following, we first provide a theoretical analysis of several conventional scheduling policies in terms of the worst case slowdown compared with the outcome of an optimal off-line scheduling policy. It is shown that the best known algorithm in the literature achieves a worst case performance ratio of 1 + 1/f(n) where f(n) =O(n^2/3) for any fixed m, which approaches to one by increasing n to the infinity. We then propose a new scheme that achieves better worst case ratio of 1 + 1/g(n) where g(n) = Θ(n/log n) for any fixed m, which approaches to one more quickly than previous schemes.

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Finding fixed points in discrete dynamical systems is important because fixed points correspond to steady-states. The Boolean network is considered as one of the simplest discrete dynamical systems and is often used as a model of genetic networks. It is known that detection of a fixed point in a Boolean network with n nodes and maximum indegree K can be polynomially transformed into (K+1)-SAT with n variables. In this paper, we focus on the case of K = 2 and present an O(1.3171ⁿ) expected time algorithm, which is faster than the naive algorithm based on a reduction to 3-SAT, where we assume that nodes with indegree 2 do not contain self-loops. We also show an algorithm for the general case of K = 2 that is slightly faster than the naive algorithm.

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When a store sells items to customers, the store wishes to decide the prices of items to maximize its profit. Intuitively, if the store sells the items with low (resp. high) prices, the customers buy more (resp. less) items, which provides less profit to the store. So it would be hard for the store to decide the prices of items. Assume that the store has a set V of n items and there is a set E of m customers who wish to buy the items, and also assume that each item i ∈ V has the production cost d_i and each customer e_j ∈ E has the valuation v_j on the bundle e_j ⊆ V of items. When the store sells an item i ∈ V at the price r_i, the profit for the item i is p_i = r_i - d_i. The goal of the store is to decide the price of each item to maximize its total profit. We refer to this maximization problem as the item pricing problem. In most of the previous works, the item pricing problem was considered under the assumption that p_i ≥ 0 for each i ∈ V, however, Balcan, et al. [In Proc. of WINE, LNCS 4858, 2007] introduced the notion of “loss-leader, ” and showed that the seller can get more total profit in the case that p_i < 0 is allowed than in the case that p_i < 0 is not allowed. In this paper, we consider the line highway problem (in which each customer is interested in an interval on the line of the items) and the cycle highway problem (in which each customer is interested in an interval on the cycle of the items), and show approximation algorithms for the line highway problem and the cycle highway problem in which the smallest valuation is s and the largest valuation is l (this is called an [s, l]-valuation setting) or all valuations are identical (this is called a single valuation setting).

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The purpose of this paper is to study sender authenticated key agreements by a third party, which uses the received parameters to verify the fact that a sender of a message knows his long-term private key. In particular, we propose a standard model for the protocol among three entities for the first time. The security of this protocol depends on the difficulty of solving two new problems related to one-way isomorphisms and the decision co-bilinear Diffie-Hellman problem on multiplicative cyclic groups. It is the first time that the security of a key agreement has been formally proven by using negligible probability. We believe that our contribution gives many applications in the cryptographic community.

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This work focuses on a vulnerability of hash functions due to sloppy usages or implementations in the real world. If our cryptographic research community succeeded in the development of a perfectly secure random function as the random oracle, it might be broken in some sense by invalid uses. In this paper, we propose a new variant of the random oracle model in order to analyze the security of cryptographic protocols under the situation of an invalid use of hash functions. Our model allows adversaries to obtain contents of the hash list of input and output pairs arbitrarily. Also, we analyze the security of several prevailing protocols (FDH, OAEP, Cramer-Shoup cryptosystem, Kurosawa-Desmedt cryptosystem, NAXOS) in our model. As the result of analyses, we clarify that FDH and Cramer-Shoup cryptosystem are still secure but others are insecure in our model. This result shows the separation between our model and the standard model.

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Shamir's (k, n)-threshold secret sharing scheme (threshold scheme) has two problems: a heavy computational cost is required to make shares and recover the secret, and a large storage capacity is needed to retain all the shares. As a solution to the heavy computational cost problem, several fast threshold schemes have been proposed. On the other hand, threshold ramp secret sharing schemes (ramp scheme) have been proposed in order to reduce each bit-size of shares in Shamir's scheme. However, there is no fast ramp scheme which has both low computational cost and low storage requirements. This paper proposes a new (k, L, n)-threshold ramp secret sharing scheme which uses just EXCLUSIVE-OR(XOR) operations to make shares and recover the secret at a low computational cost. Moreover, by proving that the fast (k, n)-threshold scheme in conjunction with a method to reduce the number of random numbers is an ideal secret sharing scheme, we show that our fast ramp scheme is able to reduce each bit-size of shares by allowing some degradation of security similar to the existing ramp schemes based on Shamir's threshold scheme.

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We explicitly describe and analyse blind hierachical identity-based encryption (blind HIBE) schemes, which are natural generalizations of blind IBE schemes [20]. We then uses the blind HIBE schemes to construct: (1) An identity-based blind signature scheme secure in the standard model, under the computational Diffie-Hellman (CDH) assumption, and with much shorter signature size and lesser communication cost, compared to existing proposals. (2) A new mechanism supporting a user to buy digital information over the Internet without revealing what he/she has bought, while protecting the providers from cheating users.

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We first consider a variant of the Schmidt-Samoa-Takagi encryption scheme without losing additively homomorphic properties. We show that this variant is secure in the sense of IND-CPA under the decisional composite residuosity assumption, and of OW-CPA under the assumption on the hardness of factoring n = p²q. Second, we introduce new algebraic properties “affine” and “pre-image restriction, ” which are closely related to homomorphicity. Intuitively, “affine” is a tuple of functions which have a special homomorphic property, and “pre-image restriction” is a function which can restrict the receiver to having information on the encrypted message. Then, we propose an encryption scheme with primitive power roots of unity in (Z/n^s+1)^×. We show that our scheme has, in addition to the additively homomorphic property, the above algebraic properties. In addition to the properties, we also show that the encryption scheme is secure in the sense of OW-CPA and IND-CPA under new number theoretic assumptions.

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This paper proposes a new sieving algorithm that employs a bucket sort as a part of a factoring algorithm such as the number field sieve. The sieving step requires an enormous number of memory updates; however, these updates usually cause cache hit misses. The proposed algorithm significantly reduces the number of cache hit misses when the size of the sieving region is roughly less than the square of the cache size, and the memory updates are several times faster than the straightforward implementation according to the PC experiments.

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This paper proposes novel algorithms for computing double-size modular multiplications with few modulus-dependent precomputations. Low-end devices such as smartcards are usually equipped with hardware Montgomery multipliers. However, due to progresses of mathematical attacks, security institutions such as NIST have steadily demanded longer bit-lengths for public-key cryptography, making the multipliers quickly obsolete. In an attempt to extend the lifespan of such multipliers, double-size techniques compute modular multiplications with twice the bit-length of the multipliers. Techniques are known for extending the bit-length of classical Euclidean multipliers, of Montgomery multipliers and the combination thereof, namely bipartite multipliers. However, unlike classical and bipartite multiplications, Montgomery multiplications involve modulus-dependent precomputations, which amount to a large part of an RSA encryption or signature verification. The proposed double-size technique simulates double-size multiplications based on single-size Montgomery multipliers, and yet precomputations are essentially free: in an 2048-bit RSA encryption or signature verification with public exponent e=2¹⁶+1, the proposal with a 1024-bit Montgomery multiplier is at least 1.5 times faster than previous double-size Montgomery multiplications.

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It is said that the lower bound of the number of iterations of Miller's algorithm for pairing calculation is log₂ r/φ(k), where φ(·) is the Euler's function, r is the group order, and k is the embedding degree. Ate pairing reduced the number of the loops of Miller's algorithm of Tate pairing from ⌊log₂ r⌋ to ⌊ log₂(t-1)⌋, where t is the Frobenius trace. Recently, it is known to systematically prepare a pairing-friendly elliptic curve whose parameters are given by a polynomial of integer variable “χ.” For such a curve, this paper gives integer variable χ-based Ate (Xate) pairing that achieves the lower bound. In the case of the well-known Barreto-Naehrig pairing-friendly curve, it reduces the number of loops to ⌊log₂χ⌋. Then, this paper optimizes Xate pairing for Barreto-Naehrig curve and shows its efficiency based on some simulation results.

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The rapid growth of the Internet provides people with tremendous opportunities for data collection, knowledge discovery and cooperative computation. However, it also brings the problem of sensitive information leakage. Both individuals and enterprises may suffer from the massive data collection and the information retrieval by distrusted parties. In this paper, we propose a privacy-preserving protocol for the distributed kernel density estimation-based clustering. Our scheme applies random data perturbation (RDP) technique and the verifiable secret sharing to solve the security problem of distributed kernel density estimation in [4] which assumed a mediate party to help in the computation.

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Transform each coordinate of the realizations of several random variables (RVs) by the distribution function of the corresponding RV and partition the range space into a uniform grid. The expected number of occupied grid-boxes will be greatest when these RVs are independent. Based on this fact, we propose a novel measure of independence named grid occupancy (GO). We also address the problem of how to make optimum selection of the parameters in GO, i.e., the number of observations and the number of quantization levels. In addition, we apply GO to independent component analysis (ICA). The GO based ICA algorithm can separate signals with arbitrary continuous distributions and favors digital hardware implementation.

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A method for accurate scene segmentation using two kinds of directed graph obtained by object matching and audio features is proposed. Generally, in audiovisual materials, such as broadcast programs and movies, there are repeated appearances of similar shots that include frames of the same background, object or place, and such shots are included in a single scene. Many scene segmentation methods based on this idea have been proposed; however, since they use color information as visual features, they cannot provide accurate scene segmentation results if the color features change in different shots for which frames include the same object due to camera operations such as zooming and panning. In order to solve this problem, scene segmentation by the proposed method is realized by using two novel approaches. In the first approach, object matching is performed between two frames that are each included in different shots. By using these matching results, repeated appearances of shots for which frames include the same object can be successfully found and represented as a directed graph. The proposed method also generates another directed graph that represents the repeated appearances of shots with similar audio features in the second approach. By combined use of these two directed graphs, degradation of scene segmentation accuracy, which results from using only one kind of graph, can be avoided in the proposed method and thereby accurate scene segmentation can be realized. Experimental results performed by applying the proposed method to actual broadcast programs are shown to verify the effectiveness of the proposed method.

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One of the most important challenges in speaker recognition is intersession variability (ISV), primarily cross-channel effects. Recent NIST speaker recognition evaluations (SRE) include a multilingual scenario with training conversations involving multilingual speakers collected in a number of other languages, leading to further performance decline. One important reason for this is that more and more researchers are using phonetic clustering to introduce high level information to improve speaker recognition. But such language dependent methods do not work well in multilingual conditions. In this paper, we study both language and channel mismatch using a support vector machine (SVM) speaker recognition system. Maximum likelihood linear regression (MLLR) transforms adapting a universal background model (UBM) are adopted as features. We first introduce a novel language independent statistical binary-decision tree to reduce multi-language effects, and compare this data-driven approach with a traditional knowledge based one. We also construct a framework for channel compensation using feature-domain latent factor analysis (LFA) and MLLR supervector kernel-based nuisance attribute projection (NAP) in the model-domain. Results on the NIST SRE 2006 1conv4w-1conv4w/mic corpus show significant improvement. We also compare our compensated MLLR-SVM system with state-of-the-art cepstral Gaussian mixture and SVM systems, and combine them for a further improvement.

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In this paper, a new approach to channel order selection of single-input multiple-output (SIMO), finite impulse response (FIR) channels is proposed for blind channel estimation. The approach utilizes cross spectral density (CSD) of the channel outputs, and minimizes the distance between two CSD's, one calculated non-parametrically from the observed output data, and the other calculated from the blindly estimated channel parameters. The CSD criterion is numerically tested on randomly generated SIMO-FIR channels, and shown to be very effective compared to existing channel order selection methods especially under low SNR settings. Blind estimates of the channels with the selected channel order also show superiority of the CSD criterion.

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Orthogonal Frequency Division Multiplexing (OFDM) transmission is robust to frequency-selective channels but sensitive to time-selective channels. Time variations of channels generate inter-carrier interference (ICI), which degrades system performance. In this paper, we develop frequency-domain Viterbi-type algorithm to effectively suppress the ICI, by exploiting the property of ICI terms in OFDM symbols. Null subcarriers, which are embedded in OFDM symbols for the reduction of interferences from/to adjacent bands, are exploited to reduce the complexity of the algorithm. Then, an approximate BER expression of Viterbi-type equalizer is derived. Simulations are provided to show the Viterbi-type equalizer works well in time- and frequency-selective (doubly selective) channel with affordable complexity.

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MIMO-OFDM is considered a key technology in emerging high-data rate systems. With MIMO techniques, the transmission quality deteriorates due to inter-antenna interference (IAI). Several signal detection schemes have been proposed to mitigate this problem. However, it is impractical to use the conventional methods without reducing theirs computational complexity. Previously, we have proposed a parallel detection algorithm using multiple QR decompositions with permuted channel matrix (MQRD-PCM) for MIMO-OFDM to reduce the system complexity. This method achieves a good BER performance with low system complexity. However, since MQRD-PCM is a kind of parallel detection method, the wrong detection probability is increased due to the bad channel SINR of the transmitted signal. As a result, the average BER performance is influenced by the wrong detection probability of the bad channel SINR. To overcome this problem, in this paper, we propose the channel ranking based joint symbols detection for MQRD-PCM/MIMO-OFDM.

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A blur restoration scheme for images with linear motion blurred objects in still background is proposed. The proposed scheme starts from a rough detection of locations of blurred objects. This rough segmentation of the blurred regions is based on an analysis of local orientation map. Then, parameters of blur are identified based on a linear constant-velocity motion blur model for every detected blurred region. After the blur parameters are estimated, the locations of blurred objects can be refined before going to a restoration process by using information from the identified blur parameters. Blur locations are refined by observing local power of the blurred image which is filtered by a high-pass filter. The high-pass filter has approximately a frequency characteristic that is complementary to the identified blur point spread function. As a final step, the image is restored by using the estimated blur parameters and locations based on an iterative deconvolution scheme applied with a regularization concept. Experimental examples of simulated and real world blurred images are demonstrated to confirm the performance of the proposed scheme.

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We propose a novel technique for estimating the number of people in a video sequence; it has the advantages of being stable even in crowded situations and needing no ground-truth data. By analyzing the geometrical relationships between image pixels and their intersection volumes in the real world quantitatively, a foreground image directly indicates the number of people. Because foreground detection is possible even in crowded situations, the proposed method can be applied in such situations. Moreover, it can estimate the number of people in an a priori manner, so it needs no ground-truth data unlike existing feature-based estimation techniques. Experiments show the validity of the proposed method.

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In this paper, an ER (Error-Reduction) algorithm-based method for removal of adherent water drops from images obtained by a rear view camera mounted on a vehicle in rainy conditions is proposed. Since Fourier-domain and object-domain constraints are needed for any ER algorithm-based method, the proposed method introduces the following two novel constraints for the removal of adherent water drops. The first one is the Fourier-domain constraint that utilizes the Fourier transform magnitude of the previous frame in the obtained images as that of the target frame. Noting that images obtained by the rear view camera have the unique characteristics of objects moving like ripples because the rear view camera is generally composed of a fish-eye lens for a wide view angle, the proposed method assumes that the Fourier transform magnitudes of the target frame and the previous frame are the same in the polar coordinate system. The second constraint is the object-domain constraint that utilizes intensities in an area of the target frame to which water drops have adhered. Specifically, the proposed method models a deterioration process of intensities that are corrupted by the water drop adhering to the rear view camera lens. By utilizing these novel constraints, the proposed ER algorithm can remove adherent water drops from images obtained by the rear view camera. Experimental results that verify the performance of the proposed method are represented.

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In this paper, a method for adaptive reconstruction of missing textures based on kernel canonical correlation analysis (CCA) with a new clustering scheme is presented. The proposed method estimates the correlation between two areas, which respectively correspond to a missing area and its neighboring area, from known parts within the target image and realizes reconstruction of the missing texture. In order to obtain this correlation, the kernel CCA is applied to each cluster containing the same kind of textures, and the optimal result is selected for the target missing area. Specifically, a new approach monitoring errors caused in the above kernel CCA-based reconstruction process enables selection of the optimal result. This approach provides a solution to the problem in traditional methods of not being able to perform adaptive reconstruction of the target textures due to missing intensities. Consequently, all of the missing textures are successfully estimated by the optimal cluster's correlation, which provides accurate reconstruction of the same kinds of textures. In addition, the proposed method can obtain the correlation more accurately than our previous works, and more successful reconstruction performance can be expected. Experimental results show impressive improvement of the proposed reconstruction technique over previously reported reconstruction techniques.

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A novel video retrieval method based on Web community extraction using audio and visual features and textual features of video materials is proposed in this paper. In this proposed method, canonical correlation analysis is applied to these three features calculated from video materials and their Web pages, and transformation of each feature into the same variate space is possible. The transformed variates are based on the relationships between visual, audio and textual features of video materials, and the similarity between video materials in the same feature space for each feature can be calculated. Next, the proposed method introduces the obtained similarities of video materials into the link relationship between their Web pages. Furthermore, by performing link analysis of the obtained weighted link relationship, this approach extracts Web communities including similar topics and provides the degree of attribution of video materials in each Web community for each feature. Therefore, by calculating similarities of the degrees of attribution between the Web communities extracted from the three kinds of features, the desired ones are automatically selected. Consequently, by monitoring the degrees of attribution of the obtained Web communities, the proposed method can perform effective video retrieval. Some experimental results obtained by applying the proposed method to video materials obtained from actual Web pages are shown to verify the effectiveness of the proposed method.

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The encoding/decoding process of JPEG2000 requires much more computation power than that of conventional JPEG mainly due to the complexity of the entropy encoding/decoding. Thus usually multiple entropy codec hardware modules are implemented in parallel to process the entropy encoding/decoding. This module, however, requests many small-size memories to store intermediate data, and when multiple modules are implemented on a chip, employment of the large number of SRAMs increases difficulty of whole chip layout. In this paper, an efficient memory organization framework for the entropy encoding/decoding module is proposed, in which not only existing memory organizations but also our proposed novel memory organization methods are attempted to expand the design space to be explored. As a result, the efficient memory organization for a target process technology can be explored.

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In the latest video coding frameworks, efficiency of motion vector (MV) coding is becoming increasingly important because of the growing bit rate portion of motion information. However, neither the conventional median predictor, nor the newer schemes such as the minimum bit rate prediction scheme and the hybrid scheme, can effectively eliminate the local redundancy of motion vectors. In this paper, we present the prioritized reference decision scheme for efficient motion vector coding, based on the H.264/AVC framework. This scheme makes use of a boolean indicator to specify whether the median predictor is to be used for the current MV or not. If not, the median prediction is considered not suitable for the current MV, and this information is used for refining the possible space of a group of reference MVs including 4 neighboring MVs and the zero MV. This group of MVs is organized to be a prioritized list so that the reference MV with highest priority is to be selected as the prediction value. Furthermore, the boolean indicators are coded into the modified code words of mb_type and sub_mb_type, so as to reduce the overhead. By applying the proposed scheme, the structure and the applicability problems with the state-of-the-art MBP scheme have been overcome. Experimental result shows that the proposed scheme achieves a considerable reduction of bits for MVDs, compared with the conventional median prediction algorithm. It also achieves a better and much stabler performance than MBP-based MV coding.

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One VLSI friendly fast motion estimation (ME) algorithm is proposed in this paper. Firstly, theoretical analysis shows that image rich of sharp edges and texture is regarded as high frequency abundant image and macroblocks (MBs) in such image will express large pixel difference. In our paper, we apply adaptive subsampling method during ME process based on pixel difference analysis, so the computation complexity of full pixel pattern can be reduced. Secondly, statistic analysis shows that for MBs with static feature, the ratio of selecting previous reference frame as best one is very high and multiple reference frame technique is not required for these MBs. Based on this analysis, we give out a block overlapping method to pick out static MBs and apply MRF elimination process. Thirdly, since many redundant search positions exist in MB with small motion trend and large search range is only contributive to MB with big motion, we extract motion feature after ME on first reference frame and use it to adjust search range for rest ME process. So, the computation complexity of redundant search positions is eliminated. Experimental results show that, compared with hardware friendly full search algorithm, our proposed algorithm can reduce 71.09% to 95.26% ME time with negligible video quality degradation. Moreover, our fast algorithm can be combined with existing fast ME algorithms like UMHexagon method for further reduction in complexity and it is friendly to hardware implementation.

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The line-based method has been one of the most commonly-used methods of hardware implementation of two-dimensional (2D) discrete wavelet transform (DWT). However, data buffer is required between the row DWT processor and the column DWT processor to solve the data flow mismatch, which increases the on-chip memory size and the output latency. Since the incompatible data flow is induced from the intrinsic property of adopted lifting-based algorithm, a decomposed lifting algorithm (DLA) is presented by rearranging the data path of lifting steps to ensure that image data is processed in raster scan manner in row processor and column processor. Theoretical analysis indicates that the precision issue of DLA outperforms other lifting-based algorithms in terms of round-off noise and internal word-length. A memory-efficient and high-performance line-based architecture is proposed based on DLA without the implementation of data buffer. For an N × M image, only 2N internal memory is required for 5/3 filter and 4N of that is required for 9/7 filter to perform 2D DWT, where N and M indicate the width and height of an image. Compared with related 2D DWT architectures, the size of on-chip memory is reduced significantly under the same arithmetic cost, memory bandwidth and timing constraint. This design was implemented in SMIC 0.18µm CMOS logic fabrication with 32kbits dual-port RAM and 20K equivalent 2-input NAND gates in a 1.00mm × 1.00mm die, which can process 512 × 512 image under 100MHz.

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Distributed Video Coding (DVC) is an emerging video coding approach, particularly attractive due to its flexibility to implement low complex encoders. This feature could be very effectively utilized in a number of video sensor based application scenarios. However, DVC is still in the process of development and currently available codec implementations are based on a number of hypothetical models and assumptions. In DVC, the effects of noise and fading on the compressed payload (parity bit stream) in real video communications and the resultant modified channel model scenario have not been discussed in literature. In this paper, a solution to the above problem in turbo coding based DVC is discussed incorporating a novel dual channel model for the maximum a-posteriori (MAP) algorithm for turbo decoding. The simulations for AWGN and wireless channels at different group of picture (GOP) sizes show that the proposed algorithm improves the rate distortion performance compared to the existing decoding algorithm. It also outperforms the H.264/AVC I-P-I-P codec (v10.1/baseline profile); particularly at low Signal to Noise Ratio (SNR) levels of the channel, thus enabling DVC as a viable and efficient option for video communications.

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This study analyzes the absolute stability in P and PD type fuzzy logic control systems with both certain and uncertain linear plants. Stability analysis includes the reference input, actuator gain and interval plant parameters. For certain linear plants, the stability (i.e. the stable equilibriums of error) in P and PD types is analyzed with the Popov or linearization methods under various reference inputs and actuator gains. The steady state errors of fuzzy control systems are also addressed in the parameter plane. The parametric robust Popov criterion for parametric absolute stability based on Lur'e systems is also applied to the stability analysis of P type fuzzy control systems with uncertain plants. The PD type fuzzy logic controller in our approach is a single-input fuzzy logic controller and is transformed into the P type for analysis. In our work, the absolute stability analysis of fuzzy control systems is given with respect to a non-zero reference input and an uncertain linear plant with the parametric robust Popov criterion unlike previous works. Moreover, a fuzzy current controlled RC circuit is designed with PSPICE models. Both numerical and PSPICE simulations are provided to verify the analytical results. Furthermore, the oscillation mechanism in fuzzy control systems is specified with various equilibrium points of view in the simulation example. Finally, the comparisons are also given to show the effectiveness of the analysis method.

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Let G(s) = C(sI - A)^-1B + D be a given system where entries of A, B, C, D are polynomials in a parameter k. Then H_∞ norm ||G(s)||_∞ of G(s) is a function of k, and [9] presents an algorithm to express 1/(||G(s)||_∞)² as a root of a bivariate polynomial, assuming feedthrough term D to be zero. This paper extends the algorithm in two ways: The first extension is the form of the function to be expressed. The extended algorithm can treat, not only H_∞ norm, but also functions that appear in the celebrated KYP Lemma. The other extension is the range of the frequency. While H_∞ norm considers the supremum of the maximum singular value of G(iω) for the infinite range 0 ≤ ω ≤ ∞ of ω, the extended algorithm treats the norm for the finite frequency range ω ≤ ω ≤ \overline{\omega}(ω, \overline{\omega} ∈ R ∪ ∞). Those two extensions allow the algorithm to be applied to wider area of control problems. We give illustrative numerical examples where we apply the extended algorithm to the computation of the frequency-restricted norm, i.e., the supremum of the maximum singular value of G(iω) (ω ≤ ω ≤ \overline{\omega}).

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In this paper, we propose a new approximate algorithm for the model predictive control (MPC) problem with a time-varying reference of hybrid systems. The proposed algorithm consists of an offline computation and an online computation. In the offline computation, candidates of mode sequences are derived. In the online computation, after the mode sequence is uniquely decided among candidates, the finite-time optimal control problem, i.e., the quadratic programming problem, is solved. So by applying the proposed algorithm, the computational amount of the online computation is decreased. First, the MPC problem with a time-varying reference is formulated. Next, the proposed algorithm is explained, and the accuracy of the obtained approximate solution is discussed. Finally, the effectiveness of the proposed method is shown by a numerical example.

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In this paper a chaotic spiking neuron is presented and its response characteristics to various periodic inputs are analyzed. A return map which can analytically describe the dynamics of the neuron is derived. Using the map, it is theoretically shown that a set of neurons can encode various periodic inputs into a set of spike-trains in such a way that a spike density of a summation of the spike-trains can approximate the waveform of the input. Based on the theoretical results, some potential applications of the presented neuron are also discussed. Using a prototype circuit, typical encoding functions of the neuron are confirmed by experimental measurements.

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This paper studies switched dynamical systems based on a simplified model of two-paralleled dc-dc buck converters in current mode control. In the system, we present novel four switching rules depending on both state variables and periodic clock. The system has piecewise constant vector field and piecewise linear solutions: they are well suited for precise analysis. We then clarify parameter conditions that guarantee generation of stable 2-phase synchronization and hyperchaos for each switching rule. Especially, it is clarified that stable synchronization is always possible by proper use of the switching rules and adjustment of clock period. Presenting a simple test circuit, typical phenomena are confirmed experimentally.

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A group signature scheme introduced by Chaum and Van Heyst allows a group member to sign messages anonymously on behalf of the group. However, in the case of a dispute, the identity of a signer of a group signature can be revealed only by a privileged entity, called a group manager. The group signature scheme has mainly been studied from the viewpoint of computational security setting so far. The main contribution of this paper is to study group signature schemes in unconditional security. More specifically, we newly introduce strong security notions of unconditionally secure group signatures (USGS for short) based on the idea of those of computationally secure group signatures proposed by Bellare, Micciancio and Warinschi. We also provide a generic method to construct USGS that is provably secure in our security definition. More precisely, we construct USGS by combining an encryption scheme with a signature, and show that the constructed scheme is unconditionally secure if the encryption and the signature used in the construction are unconditionally secure. Finally, we provide an instantiation of the one-time secure group signature scheme based on the generic construction.

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In this paper, we extend the conventional error-trellis construction for convolutional codes to the case where a given check matrix H(D) has a factor D^l in some column (row). In the first case, there is a possibility that the size of the state space can be reduced using shifted error-subsequences, whereas in the second case, the size of the state space can be reduced using shifted syndrome-subsequences. The construction presented in this paper is based on the adjoint-obvious realization of the corresponding syndrome former H^T(D). In the case where all the columns and rows of H(D) are delay free, the proposed construction is reduced to the conventional one of Schalkwijk et al. We also show that the proposed construction can equally realize the state-space reduction shown by Ariel et al. Moreover, we clarify the difference between their construction and that of ours using examples.

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In this paper, we present a low complexity, yet accurate adaptive algorithm for the tracking of two-dimensional (2-D) direction of arrival (DOAs) based on a uniform rectangular array (URA). The new algorithm is a novel hybrid of tracking and beamforming processes by making use of three stages of one-dimensional (1-D) DOA tracking algorithms — in a hierarchical tree structure — to determine the two DOA components iteratively in a coarse-fine manner. In between every other 1-D DOA tracking algorithm, a complementary orthogonal beamforming process is invoked to partition the incoming signals into appropriate groups to enhance the tracking accuracy. Since the new algorithm only involves the 1-D subspace-based DOA tracking algorithm, the overall complexity is substantially less than the direct two-dimensional (2-D) extension of the existing 1-D DOA tracking algorithms, which requires an update of higher-dimensional vectors followed by a higher-dimensional eigendecomposition or a 2-D search. Furthermore, with the tree-structured DOA tracking scheme, the tracked 2-D DOA components are automatically paired without extra computational overhead. Furnished simulations show that the new algorithm can provide satisfactory tracking performance in various scenarios.

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This paper introduces a multilayer traffic network model and traffic network clustering method for solving the route selection problem (RSP) in car navigation system (CNS). The purpose of the proposed method is to reduce the computation time of route selection substantially with acceptable loss of accuracy by preprocessing the large size traffic network into new network form. The proposed approach further preprocesses the traffic network than the traditional hierarchical network method by clustering method. The traffic network clustering considers two criteria. We specify a genetic clustering algorithm for traffic network clustering and use NSGA-II for calculating the multiple objective Pareto optimal set. The proposed method can overcome the size limitations when solving route selection in CNS. Solutions provided by the proposed algorithm are compared with the optimal solutions to analyze and quantify the loss of accuracy.

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In this letter, we propose a speech reinforcement technique based on soft decision under both the far-end and near-end noise environments. We amplify the estimated clean speech signal at the far-end based on the estimated ambient noise spectrum at the near-end, as opposed to reinforcing the noisy far-end speech signal, so that it can be heard more intelligibly in far-end noisy environments. To obtain an effective reinforcement technique, we adopt the soft decision scheme incorporating a speech absence probability (SAP) in the frequency dependent signal-to-noise ratio (SNR) recovery method where the clean speech spectrum is estimated and the reinforcement gain is inherently derived and modified within the unified framework. Performance of the proposed method is evaluated by a subjective testing under various noisy environments. This is an improvement over previous approaches.

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In this letter, we propose an efficient method to improve the performance of voiced/unvoiced (V/UV) sounds decision for the selectable mode vocoder (SMV) of 3GPP2 using the Gaussian mixture model (GMM). We first present an effective analysis of the features and the classification method adopted in the SMV. And feature vectors which are applied to the GMM are then selected from relevant parameters of the SMV for the efficient V/UV classification. The performance of the proposed algorithm are evaluated under various conditions and yield better results compared to the conventional method of the SMV.

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This letter presents recursive frequency offset estimation for MIMO (Multiple Input Multiple Output) system in flat-fading channels. With the recursive estimation, the frequency offset range in MIMO system can be extended compared with normal estimation. Simulation results show that the recursive frequency offset estimation is valid for large frequency offset.

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A simple and novel residual acoustic echo cancellation method that employs binary masking is proposed to enhance the speech quality of hands-free communication in an automobile environment. In general, the W-disjoint orthogonality assumption is used for blind source separation using multi-microphones. However, in this Letter, it is utilized to mask the residual echo component in the time-frequency domain using a single microphone. The experimental results confirm the effectiveness of the proposed method in terms of the echo return loss enhancement and speech enhancement.

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A rotary inverted pendulum is stabilized by a single first order dynamic output feedback system. Numerical simulations and experimental results show that the proposed control law has low-pass filter property as well as it can successfully replace the velocity measurements for LQR control law.

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In this letter the complexity of factoring an α-LSBS modulus is analyzed. This gives an improvement on the lower bound of the previous results.

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A quaternary sequence is constructed by Gray mapping of a binary sequence with even period and its shift. The autocorrelation of the new quaternary sequence is the same as that of the binary sequence employed. Quaternary sequences with the maximum autocorrelation 2 can be obtained by the construction for period N ≡ 2 (mod 4).

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We show the sufficient conditions for coding by nodes such that every sink can decode all information multicasted by the single source when there exists time-varying delay of information transmission at links in the network coding.

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A direct short proof of Horiguchi's formula for error values in alternant codes is provided. Horiguchi's formula employs only output polynomials of Berlekamp-Massey algorithm, which has less computational complexity than extended Euclidean algorithm for decoding alternant codes. As an application of our proof, we provide an explicit formula for the generator and parity check matrices of alternant codes and their singly- and doubly-extended codes.

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