In this paper, we propose an algorithm that enhances the number of pixels for high-speed imaging. High-speed cameras have a principle problem that the number of pixels reduces when the number of frames per second (fps) increases. To enhance the number of pixels, we suppose an optical structure that block-randomly selects some percent of pixels in an image. Then, we need to reconstruct the entire image. For this, a state-of-the-art method takes three-dimensional reconstruction strategy, which requires a heavy computational cost in terms of time. To reduce the cost, the proposed method reconstructs the entire image frame-by-frame using a new cost function exploiting two types of sparsity. One is within each frame and the other is induced from the similarity between adjacent frames. The latter further means not only in the image domain, but also in a sparsifying transformed domain. Since the cost function we define is convex, we can find the optimal solution using a convex optimization technique with small computational cost. We conducted simulations using grayscale image sequences. The results show that the proposed method produces a sequence, mostly the same quality as the state-of-the-art method, with dramatically less computational time.

Second-order sampling of 2-D frequency distributions is examined in this paper. When a figure in the frequency space can fill up the entire frequency space by tiling, we call this figure a tiling cluster. We also introduce the concept of pair regions. The results obtained for the second-order sampling of 1-D and 2-D frequency distributions are arranged using these two concepts. The sampling functions and sampling positions of second-order sampling of a 2-D rectangular-complement highpass frequency distribution, which have not been solved until now, are explicitly presented by using these two concepts.

Spritz is a stream cipher proposed by Rivest and Schuldt at the rump session of CRYPTO 2014. It is intended to be a replacement of the popular RC4 stream cipher. In this paper we propose distinguishing attacks on the full Spritz, based on a short-term bias in the first two bytes of a keystream and a long-term bias in the first two bytes of every cycle of N keystream bytes, where N is the size of the internal permutation. Our attacks are able to distinguish a keystream of the full Spritz from a random sequence with samples of first two bytes produced by 2^44.8 multiple key-IV pairs or 2^60.8 keystream bytes produced by a single key-IV pair. These biases are also useful in the event of plaintext recovery in a broadcast attack. In the second part of the paper, we look at a state recovery attack on Spritz, in a special situation when the cipher enters a class of weak states. We determine the probability of encountering such a state, and demonstrate a state recovery algorithm that betters the 2¹⁴⁰⁰ step algorithm of Ankele et al. at Latincrypt 2015. Finally we propose a simple fix that removes the bias in the first two keystream bytes. The countermeasure requires only one additional memory access and hence does not diminish software performance substantially, and in fact the loss in software speed is only around 1.5%.

This contribution presents and analyzes the statistical regularity related to the noise power spectrum series and the speech spectrum series. It also undertakes a thorough inquiry of the quasi-Gaussian distributed power spectrum series obtained using the radical root transformation. Consequently, a noise-estimation algorithm is proposed for speech enhancement. This method is effective for separating the noise power spectrum from the noisy speech power spectrum. In contrast to standard noise-estimation algorithms, the proposed method requires no speech activity detector. It was confirmed to be conceptually simple and well suited to real-time implementations. Practical experiment tests indicated that our method is preferred over previous methods.

In this paper, MWAN (Mobile Wireless Ad hoc Networks with internet connection) is considered, which is a solution for many tasks owing to its ease of use, and practicality. Recently, MWAN is required to support large data like multimedia data transfer and it is transferred through several relay nodes. There are 2 problems that cause difficulties for large data transfer through a mobile network. First one is rerouting delay by handoff and second one is network congestion caused by handoff. Also, faulty data transfer caused by handoff delay makes extra load and causes some problems for MWAN. To solve these problems and get network reliability, we propose a new multipath routing scheme that can provide solution for seamless connection while handoff. In the proposed scheme, our MWAN can support multiple paths for data transfer, maintain end-to-end connection while handoff and get new route quickly. The performance of the proposed scheme is evaluated and compared with other multipath routing scheme to show the improvement.

Particle filter algorithm is an important algorithm in the field of target tracking. however, this algorithm faces the problem of sample impoverishment which is caused by the introduction of re-sampling and easily affected by illumination variation. This problem seriously affects the tracking performance of a particle filter algorithm. To solve this problem, we introduce a particle filter target tracking algorithm based on a dynamic niche genetic algorithm. The application of this dynamic niche genetic algorithm to re-sampling ensures particle diversity and dynamically fuses the color and profile features of the target in order to increase the algorithm accuracy under the illumination variation. According to the test results, the proposed algorithm accurately tracks the target, significantly increases the number of particles, enhances the particle diversity, and exhibits better robustness and better accuracy.

This letter presents a novel memory-based architecture for radix-2 fast Walsh-Hadamard-Fourier transform (FWFT) based on the constant geometry FWFT algorithm. It is composed of a multi-function Processing Engine, a conflict-free memory addressing scheme and an efficient twiddle factor generator. The address for memory access and the control signals for stride permutation are formulated in detail and the methods can be applied to other memory-based FFT-like architectures.

The massive multiple input multiple output (MIMO) system with large-scale antenna array at base station (BS) simultaneously communicates with many mobile stations (MSs) ensuring high reliability using the pre-coding. But, in mobile communication, the performance of the pre-coding is degraded by fast fading. For improving the performance of the pre-coding, this letter proposes the power control scheme of the new approach that has the variable step size using the statistical characteristic of fast fading and Doppler frequency. From the simulation results, it is shown that the proposed scheme improves signal-to-interference-plus-noise ratio (SINR) performance.

Locally repairable codes (LRCs) have attracted much interest recently due to their applications in distributed storage systems. In an [n,k,d] linear code, a code symbol is said to have locality r if it can be repaired by accessing at most r other code symbols. An (n,k,r) LRC with locality r for the information symbols has minimum distance d≤n-k-⌈k/r⌉+2. In this letter, we study single-parity LRCs where every repair group contains exactly one parity symbol. Firstly, we give a new characterization of single-parity LRCs based on the standard form of generator matrices. For the optimal single-parity LRCs meeting the Singleton-like bound, we give necessary conditions on the structures of generator matrices. Then we construct all the optimal binary single-parity LRCs meeting the Singleton-like bound d≤n-k-⌈k/r⌉+2.

Let $R$ = $\mathbb{F}_{p}+u\mathbb{F}_{p}+v\mathbb{F}_{p}+uv\mathbb{F}_{p}$, where u²=u, v² and uv=vu. A relation between the support weight distribution of a linear code $\mathscr{C}$ of type p^4k over R and its dual code $\mathscr{C}^{\bot}$ is established.

This letter considers the robust transceiver design for multiple-input multiple-output interference channels under channel state information mismatch. According to alternating schemes, an adaptive algorithm is proposed to solve the minimum SINR maximization problem. Simulation results show the convergence and the effectiveness of the proposed algorithm.

This letter introduces a new model for backscatter assisted wireless powered communication networks (BAWPCNs) that include a hybrid access point (HAP) and multiple backscatter communication (BackCom) and traditional wireless powered communication network (WPCN) users. To make full use of time to transmit information, both backscatter and harvest-then-transmit (HTT) modes are employed. In the proposed model, during the first time slot dedicated for energy transfer in traditional WPCNs, the traditional WPCN users harvest energy radiated by the HAP, and simultaneously the BackCom users reflect modulated signals to the HAP. The traditional WPCN users are scheduled during the remaining time slots via time division multiple access (TMDA). The optimal time allocation policies for the half-duplex (HD) and full-duplex (FD) BAWPCNs are obtained to maximize the system throughput. The tradeoff between backscatter and HTT modes is analyzed. Simulation results demonstrate the superiority of the proposed model.

Multiple image group cosegmentation (MGC) aims at segmenting common object from multiple group of images, which is a new cosegmentation research topic. The existing MGC methods formulate MGC as label assignment problem (Markov Random Field framework), which is observed to be sensitive to parameter setting. Meanwhile, it is also observed that large object variations and complicated backgrounds dramatically decrease the existing MGC performance. To this end, we propose a new object proposal based MGC model, with the aim of avoiding tedious parameter setting, and improving MGC performance. Our main idea is to formulate MGC as new region proposal selection task. A new energy function in term of proposal is proposed. Two aspects such as the foreground consistency within each single image group, and the group consistency among image groups are considered. The energy minimization method is designed in EM framework. Two steps such as the loop belief propagation and foreground propagation are iteratively implemented for the minimization. We verify our method on ICoseg dataset. Six existing cosegmentation methods are used for the comparison. The experimental results demonstrate that the proposed method can not only improve MGC performance in terms of larger IOU values, but is also robust to the parameter setting.