IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Online ISSN : 1745-1337
Print ISSN : 0916-8508
Current issue
Displaying 1-11 of 11 articles from this issue
Regular Section
  • Yiqi CHEN, Ping WEI, Gaiyou LI, Huaguo ZHANG, Hongshu LIAO
    Article type: PAPER
    Subject area: Digital Signal Processing
    2022 Volume E105.A Issue 12 Pages 1522-1536
    Published: December 01, 2022
    Released on J-STAGE: December 01, 2022
    Advance online publication: June 08, 2022
    JOURNAL FREE ACCESS

    This paper considers tracking of a non-cooperative emitter based on a single sensor. To this end, the direct target motion analysis (DTMA) approach, where the target state is straightforwardly achieved from the received signal, is exploited. In order to achieve observability, the sensor has to perform a maneuver relative to the emitter. By suitably building an approximated likelihood function, the unscented Kalman filter (UKF), which is able to work under high nonlinearity of the measurement model, is adopted to recursively estimate the target state. Besides, the posterior Cramér-Rao bound (PCRB) of DTMA, which can be used as performance benchmark, is also achieved. The effectiveness of proposed method is verified via simulation experiments.

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  • Phuong T.K. DINH, Linh T.T. DINH, Tung T. TRAN, Lam S. PHAM, Han Le DU ...
    Article type: PAPER
    Subject area: Digital Signal Processing
    2022 Volume E105.A Issue 12 Pages 1537-1550
    Published: December 01, 2022
    Released on J-STAGE: December 01, 2022
    Advance online publication: June 17, 2022
    JOURNAL FREE ACCESS

    Recently, most signal processing algorithms have been developed with floating-point arithmetic, while the fixed-point arithmetic is more popular with most commercial devices and low-power real-time applications which are implemented on embedded/ASIC/FPGA systems. Therefore, the optimal Floating-point to Fixed-point Conversion (FFC) methodology is a promising solution. In this paper, we propose the FFC consisting of signal grouping technique and simulation-based word length optimization. In order to evaluate the performance of the proposed technique, simulations are carried out and hardware co-simulation on Field Programmable Gate Arrays (FPGAs) platform have been applied to complex Digital Signal Processing (DSP) algorithms: Linear Time Invariant (LTI) systems, multi-mode Fast Fourier Transform (FFT) circuit for IEEE 802.11 ax WLAN Devices and the calibration algorithm of gain and clock skew in Time-Interleaved ADC (TI-ADC) using Adaptive Noise Canceller (ANC). The results show that the proposed technique can reduce the hardware cost about 30% while being able to maintain its speed and reliability.

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  • Kaizhan LIN, Fangguo ZHANG, Chang-An ZHAO
    Article type: PAPER
    Subject area: Cryptography and Information Security
    2022 Volume E105.A Issue 12 Pages 1551-1558
    Published: December 01, 2022
    Released on J-STAGE: December 01, 2022
    Advance online publication: May 30, 2022
    JOURNAL FREE ACCESS

    Supersingular isogeny Diffie-Hellman (SIDH) is attractive for its relatively small public key size, but it is still unsatisfactory due to its efficiency, compared to other post-quantum proposals. In this paper, we focus on the performance of SIDH when the starting curve is E6 : y2 = x3 + 6x2 + x, which is fixed in Round-3 SIKE implementation. Inspired by previous works [1], [2], we present several tricks to accelerate key generation of SIDH and each process of SIKE. Our experimental results show that the performance of this work is at least 6.09% faster than that of the SIKE implementation, and we can further improve the performance when large storage is available.

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  • Yohei WATANABE, Takeshi NAKAI, Kazuma OHARA, Takuya NOJIMA, Yexuan LIU ...
    Article type: PAPER
    Subject area: Cryptography and Information Security
    2022 Volume E105.A Issue 12 Pages 1559-1577
    Published: December 01, 2022
    Released on J-STAGE: December 01, 2022
    Advance online publication: May 25, 2022
    JOURNAL FREE ACCESS

    Searchable symmetric encryption (SSE) enables clients to search encrypted data. Curtmola et al. (ACM CCS 2006) formalized a model and security notions of SSE and proposed two concrete constructions called SSE-1 and SSE-2. After the seminal work by Curtmola et al., SSE becomes an active area of encrypted search. In this paper, we focus on two unnoticed problems in the seminal paper by Curtmola et al. First, we show that SSE-2 does not appropriately implement Curtmola et al.'s construction idea for dummy addition. We refine SSE-2's (and its variants') dummy-adding procedure to keep the number of dummies sufficiently many but as small as possible. We then show how to extend it to the dynamic setting while keeping the dummy-adding procedure work well and implement our scheme to show its practical efficiency. Second, we point out that the SSE-1 can cause a search error when a searched keyword is not contained in any document file stored at a server and show how to fix it.

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  • Hiroaki YAMAMOTO, Ryosuke ODA, Yoshihiro WACHI, Hiroshi FUJIWARA
    Article type: PAPER
    Subject area: Cryptography and Information Security
    2022 Volume E105.A Issue 12 Pages 1578-1590
    Published: December 01, 2022
    Released on J-STAGE: December 01, 2022
    Advance online publication: June 08, 2022
    JOURNAL FREE ACCESS

    A searchable symmetric encryption (SSE) scheme is a method that searches encrypted data without decrypting it. In this paper, we address the substring search problem such that for a set D of documents and a pattern p, we find all occurrences of p in D. Here, a document and a pattern are defined as a string. A directed acyclic word graph (DAWG), which is a deterministic finite automaton, is known for solving a substring search problem on a plaintext. We improve a DAWG so that all transitions of a DAWG have distinct symbols. Besides, we present a space-efficient and secure substring SSE scheme using an improved DAWG. The proposed substring SSE scheme consists of an index with a simple structure, and the size is O(n) for the total size n of documents.

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  • Haiyang ZOU, Wengang ZHAO
    Article type: PAPER
    Subject area: Information Theory
    2022 Volume E105.A Issue 12 Pages 1591-1603
    Published: December 01, 2022
    Released on J-STAGE: December 01, 2022
    Advance online publication: June 20, 2022
    JOURNAL FREE ACCESS

    It has been widely recognized that in compressed sensing, many restricted isometry property (RIP) conditions can be easily obtained by using the null space property (NSP) with its null space constant (NSC) 0<θ≤1 to construct a contradicted method for sparse signal recovery. However, the traditional NSP with θ=1 will lead to conservative RIP conditions. In this paper, we extend the NSP with 0<θ<1 to a scale NSP, which uses a factor τ to scale down all vectors belonged to the Null space of a sensing matrix. Following the popular proof procedure and using the scale NSP, we establish more relaxed RIP conditions with the scale factor τ, which guarantee the bounded approximation recovery of all sparse signals in the bounded noisy through the constrained 1 minimization. An application verifies the advantages of the scale factor in the number of measurements.

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  • Mayuna TOBE, Sou NOBUKAWA
    Article type: PAPER
    Subject area: Neural Networks and Bioengineering
    2022 Volume E105.A Issue 12 Pages 1604-1611
    Published: December 01, 2022
    Released on J-STAGE: December 01, 2022
    Advance online publication: June 03, 2022
    JOURNAL FREE ACCESS

    Various types of indices for estimating functional connectivity have been developed over the years that have introduced effective approaches to discovering complex neural networks in the brain. Two significant examples are the phase lag index (PLI) and transfer entropy (TE). Both indices have specific benefits; PLI, defined using instantaneous phase dynamics, achieves high spatiotemporal resolution, whereas transfer entropy (TE), defined using information flow, reveals directed network characteristics. However, the relationship between these indices remains unclear. In this study, we hypothesize that there exists a complementary relationship between PLI and TE to discover new aspects of functional connectivity that cannot be detected using either PLI or TE. To validate this hypothesis, we evaluated the synchronization in a coupled Rössler model using PLI and TE. Consequently, we proved the existence of non-linear relationships between PLI and TE. Both indexes exhibit a specific trend that demonstrates a linear relationship in the region of small TE values. However, above a specific TE value, PLI converges to a constant irrespective of the TE value. In addition to this relational difference in synchronization, there is another characteristic difference between these indices. Moreover, by virtue of its finer temporal resolution, PLI can capture the temporal variability of the degree of synchronization, which is called dynamical functional connectivity. TE lacks this temporal characteristic because it requires a longer evaluation period in this estimation process. Therefore, combining the advantages of both indices might contribute to revealing complex spatiotemporal functional connectivity in brain activity.

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  • Xiuping PENG, Mingshuo SHEN, Hongbin LIN, Shide WANG
    Article type: LETTER
    Subject area: Digital Signal Processing
    2022 Volume E105.A Issue 12 Pages 1612-1615
    Published: December 01, 2022
    Released on J-STAGE: December 01, 2022
    Advance online publication: May 26, 2022
    JOURNAL FREE ACCESS

    This letter provides a direct construction of binary even-length Z-complementary pairs. To date, the maximum zero correlation zone ratio of Type-I Z-complementary pairs has reached 6/7, but no direct construction of Z-complementary pairs can achieve the zero correlation zone ratio of 6/7. In this letter, based on Boolean function, we give a direct construction of binary even-length Z-complementary pairs with zero correlation zone ratio 6/7. The length of constructed Z-complementary pairs is 2m+3 + 2m + 2+2m+1 and the width of zero correlation zone is 2m+3 + 2m+2.

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  • Hangjin SUN, Lei WANG, Zhaoyang QIU, Qi ZHANG
    Article type: LETTER
    Subject area: Digital Signal Processing
    2022 Volume E105.A Issue 12 Pages 1616-1620
    Published: December 01, 2022
    Released on J-STAGE: December 01, 2022
    Advance online publication: May 24, 2022
    JOURNAL FREE ACCESS

    The Nyquist folding receiver (NYFR) is a novel analog-to-information architecture, which can achieve wideband receiving with a small amount of system resource. The NYFR uses a radio frequency (RF) non-uniform sampling to realize wideband receiving, and the practical RF non-uniform sample pulse train usually contains an aperture. Therefore, it is necessary to investigate the aperture impact on the NYFR output. In this letter, based on the NYFR output signal to noise ratio (SNR), the aperture impact on the NYFR is analyzed. Focusing on the aperture impact, the corresponding NYFR output signal power and noise power are given firstly. Then, the relation between the aperture and the output SNR is analyzed. In addition, the output SNR distribution containing the aperture is investigated. Finally, combing with a parameter estimation method, several simulations are conducted to prove the theoretical aperture impact.

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  • Tongwei LU, Hao ZHANG, Feng MIN, Shihai JIA
    Article type: LETTER
    Subject area: Image
    2022 Volume E105.A Issue 12 Pages 1621-1625
    Published: December 01, 2022
    Released on J-STAGE: December 01, 2022
    Advance online publication: May 24, 2022
    JOURNAL FREE ACCESS

    Convolutional neural network (CNN) based vehicle re-identificatioin (ReID) inevitably has many disadvantages, such as information loss caused by downsampling operation. Therefore we propose a vision transformer (Vit) based vehicle ReID method to solve this problem. To improve the feature representation of vision transformer and make full use of additional vehicle information, the following methods are presented. (I) We propose a Quadratic Split Architecture (QSA) to learn both global and local features. More precisely, we split an image into many patches as “global part” and further split them into smaller sub-patches as “local part”. Features of both global and local part will be aggregated to enhance the representation ability. (II) The Auxiliary Information Embedding (AIE) is proposed to improve the robustness of the model by plugging a learnable camera/viewpoint embedding into Vit. Experimental results on several benchmarks indicate that our method is superior to many advanced vehicle ReID methods.

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  • TongWei LU, ShiHai JIA, Hao ZHANG
    Article type: LETTER
    Subject area: Vision
    2022 Volume E105.A Issue 12 Pages 1626-1630
    Published: December 01, 2022
    Released on J-STAGE: December 01, 2022
    Advance online publication: May 24, 2022
    JOURNAL FREE ACCESS

    At this stage, research in the field of Few-shot image classification (FSC) has made good progress, but there are still many difficulties in the field of Few-shot object detection (FSOD). Almost all of the current FSOD methods face catastrophic forgetting problems, which are manifested in that the accuracy of base class recognition will drop seriously when acquiring the ability to recognize Novel classes. And for many methods, the accuracy of the model will fall back as the class increases. To address this problem we propose a new memory-based method called Memorable Faster R-CNN (MemFRCN), which makes the model remember the categories it has already seen. Specifically, we propose a new tow-stage object detector consisting of a memory-based classifier (MemCla), a fully connected neural network classifier (FCC) and an adaptive fusion block (AdFus). The former stores the embedding vector of each category as memory, which enables the model to have memory capabilities to avoid catastrophic forgetting events. The final part fuses the outputs of FCC and MemCla, which can automatically adjust the fusion method of the model when the number of samples increases so that the model can achieve better performance under various conditions. Our method can perform well on unseen classes while maintaining the detection accuracy of seen classes. Experimental results demonstrate that our method outperforms other current methods on multiple benchmarks.

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