In this paper, we propose a method capable of shortening the distance from a noise detection microphone to a loudspeaker in active noise control system with non-minimum phase secondary path. The distance can be basically shortened by forming the noise control filter, which produces the secondary noise provided by the loudspeaker, with the cascade connection of a non-recursive filter and a recursive filter. The output of the recursive filter, however, diverges even when the secondary path includes only a minimum phase component. In this paper, we prevent the divergence by utilizing MINT (multi-input/output inverse theorem) method increasing the number of secondary paths than that of primary paths. MINT method, however, requires a large scale inverse matrix operation, which increases the processing cost. We hence propose a method reducing the processing cost. Actually, MINT method has only to be applied to the non-minimum phase components of the secondary paths. We hence extract the non-minimum phase components and then apply MINT method only to those. The order of the inverse matrix thereby decreases and the processing cost can be reduced. We finally show a simulation result demonstrating that the proposed method successfully works.

In this paper, time-difference estimation of filtered random signals passed through multipath channels is discussed. First, we reformulate the approach based on innovation-rate sampling (IRS) to fit our random signal model, then use the IRS results to drive the nonlinear least-squares (NLS) minimization algorithm. This hybrid approach (referred to as the IRS-NLS method) provides consistent estimates even for cases with sub-Nyquist sampling assuming the use of compactly-supported sampling kernels that satisfies the recently-developed nonaliasing condition in the frequency domain. Numerical simulations show that the proposed NLS-IRS method can improve performance over the straight-forward IRS method, and provides approximately the same performance as the NLS method with reduced sampling rate, even for closely-spaced time delays. This enables, given a fixed observation time, significant reduction in the required number of samples, while maintaining the same level of estimation performance.

A generalized version of a piece-wise constant (ab. PWC) spiking neuron model is presented. It is shown that the generalization enables the model to reproduce 20 activities in the Izhikevich model. Among the activities, we analyze tonic bursting. Using an analytical one-dimensional iterative map, it is shown that the model can reproduce a burst-related bifurcation scenario, which is qualitatively similar to that of the Izhikevich model. The bifurcation scenario can be observed in an actual hardware.

We propose a generic conversion from a key encapsulation mechanism (KEM) to an identification (ID) scheme. The conversion derives the security for ID schemes against concurrent man-in-the-middle (cMiM) attacks from the security for KEMs against adaptive chosen ciphertext attacks on one-wayness (one-way-CCA2). Then, regarding the derivation as a design principle of ID schemes, we develop a series of concrete one-way-CCA2 secure KEMs. We start with El Gamal KEM and prove it secure against non-adaptive chosen ciphertext attacks on one-wayness (one-way-CCA1) in the standard model. Then, we apply a tag framework with the algebraic trick of Boneh and Boyen to make it one-way-CCA2 secure based on the Gap-CDH assumption. Next, we apply the CHK transformation or a target collision resistant hash function to exit the tag framework. And finally, as it is better to rely on the CDH assumption rather than the Gap-CDH assumption, we apply the Twin DH technique of Cash, Kiltz and Shoup. The application is not “black box” and we do it by making the Twin DH technique compatible with the algebraic trick. The ID schemes obtained from our KEMs show the highest performance in both computational amount and message length compared with previously known ID schemes secure against concurrent man-in-the-middle attacks.

It is known that the optimal sensor coverage of a mission space is performed by a Voronoi partition, which is called a Voronoi coverage problem. We consider the case that the mission space has several obstacles where mobile sensors cannot be deployed and search an optimal deployment to maximize the sensing performance. Inspired by the potential field method, we introduce a repulsive potential for obstacle avoidance and define the objective function by a combination of two functions: one for evaluation of the sensing performance and the other for obstacle avoidance. We introduce a space where a sensor can move, called its moving space. In general, a moving space may not coincide with the mission space. We assume that the respective moving spaces of each sensor may differ from each other. By introducing a barycentric coordinate over the moving space, we show that the Voronoi coverage problem to maximize the objective function is transformed into a potential game. In potential games, local maximizers of a potential function are stable equilibrium points of the corresponding replicator dynamics. We propose a distributed sensor coverage control method based on the replicator dynamics to search a local maximizer of the objective function and a path to it. Using simulations, we also compare the proposed method with the Lloyd and TangentBug algorithm proposed by Breitenmoser et al.

The radio frequency identification (RFID) system has attracting attention as a new identification source that achieves a ubiquitous environment. Each RFID tag has a unique ID code, and is attached on an object whose information it contains. A user reads the unique ID code using RFID readers and obtains information about the object. One of the important applications of RFID technology is the indoor position estimation of RFID tags. It can be applied to navigation systems for people in complex buildings. In this paper, we propose an effective position estimation method named Broad-type Multi-Sensing-Range (B-MSR) method to improve the estimation error of the conventional methods using sensor model. A new reader antenna with two flexible antenna elements is introduced into B-MSR. The distance between two flexible antenna elements can be adjusted. Thus, two kinds of system parameters can be controlled, the distance between two antenna elements and the transmission power of the RFID reader. In this paper, four sensing ranges are settled by controlling the values of two parameters. The performance evaluation shows four characteristics of B-MSR. Firstly, it reduces the initial estimation error. Secondly, it reduces the moving distance. Thirdly, it reduces the number of different sensing points. Fourthly, it shortens the required estimation time.

The hyper H_∞ filter derived in our previous work provides excellent convergence, tracking, and robust performances for linear time-varying system identification. Additionally, a fast algorithm of the hyper H_∞ filter, called the fast H_∞ filter, is successfully developed so that identification of linear system with impulse response of length N is performed at a computational complexity of O(N). The gain matrix of the fast filter is recursively calculated through estimating the forward and backward linear prediction coefficients of an input signal. This suggests that the fast H_∞ filter may be applicable to linear prediction of the signal. On the other hand, an alternative fast version of the hyper H_∞ filter, called the J-fast H_∞ filter, is derived using a J-unitary array form, which is amenable to parallel processing. However, the J-fast H_∞ filter explicitly includes no linear prediction of input signals in the algorithm. This work reveals that the forward and backward linear prediction coefficients and error powers of the input signal are indeed included in the recursive variables of the J-fast H_∞ filter. These findings are verified by computer simulations.

In this paper, an improved hybrid LUT-based architecture for low-error and efficient fixed-width squarer circuits is presented in which LUT-based and conventional logic circuits are employed together to achieve the good trade-off between hardware complexity and performance. By exploiting the mathematical identities and hybrid architecture, the mean error and mean squarer error of the proposed squarer are reduced by up to 40%, compared with the best previous method presented in literature. Moreover, the proposed method can improve the speed and reduce the area of the squarer circuit. The implementation and chip measurement results in 0.18-µm CMOS technology are also presented and discussed.

A flexible and computationally efficient method for spectral analysis of sinusoidal signals using the Basis Pursuit De-Noising (BPDN) is proposed. This method estimates a slotted Auto-Correlation Function (ACF) and computes the spectrum as the sparse representation of the ACF in a dictionary of cosine functions. Simulation results illustrate flexibility and effectiveness of the proposed method.

In this comment, an inequality of algebraic immunity of the sum of two Boolean functions is pointed out to be generally incorrect. Then we present some results on how to impose conditions such that the inequality is true. Finally, complete proofs of two existing results are given.

In this letter, a novel steganographic method with four-pixel differencing and exploiting modification direction is proposed. Secret data are embedded into each four-pixel block by adaptively applying exploiting modification direction technique. The difference value of the four-pixel block is used to judge whether the pixels in edge areas can tolerate larger changes than those in smooth areas. The readjustment guarantees to extract the secret data exactly and to minimize the embedding distortion. Since the proposed method processes non-overlapping 22 pixels blocks instead of two consecutive pixels, the features of edge can be considered sufficiently. Compared with the previous method, experimental results show that the proposed method provides better performance, i.e., larger embedding capacity and better image quality.

An important concept in secret sharing scheme is the access structure. However, determining the access structure of the secret sharing scheme based on a linear code is a very difficult problem. In this work, we provide a method to construct a class of two-weight linear codes over finite rings. Based on the two-weight codes, we present an access structure of a secret sharing scheme.

We define a family of 2^e+1-periodic binary threshold sequences and a family of p²-periodic binary threshold sequences by using Carmichael quotients modulo 2^e (e > 2) and 2p (p is an odd prime), respectively. These are extensions of the construction derived from Fermat quotients modulo an odd prime in our earlier work. We determine exact values of the linear complexity, which are larger than half of the period. For cryptographic purpose, the linear complexities of the sequences in this letter are of desired values.

This letter investigates the training convergence in range-based cooperative positioning with stochastic positional knowledge. Firstly, a closed-form of squared position-error bound (SPEB) is derived with error-free ranging. Using the derived closed-form, it is proved that the SPEB reaches its minimum when at least 2 out of N (> 2) agents send training sequences. Finally, numerical results are provided to elaborate the theoretical analysis with zero-mean Gaussian ranging errors.

In our previous research, to achieve unequal error protection (UEP), we proposed a scheme which encodes the data by randomly switching between several codes which use different signal constellations and showed the effectiveness in AWGN channels. In this letter, we propose our UEP system using MMSE-FDE for fast and selective fading by using the fact that importance levels are changed every few symbols, i.e., every block, in the proposed system. We confirmed the improvement in BER performance and the effectiveness of adaptive equalization for the proposed system in fading channels. Moreover, in fading channels we confirmed the validity of the theoretical tradeoff shown in static conditions.

The applications of dynamic content updates for a group of users, for example weather reports and news broadcast, have been shown to benefit significantly from Delay Tolerant Networks (DTNs) communication mechanisms. In this paper, we study the performance of dynamic content updates over DTNs by focusing on the latest content distribution, which is an important factor of the system energy consumption and content update efficiency. By characterizing the content generating process and content sharing process, we obtain an explicit expression for the latest content distribution, and prove it theoretically. Moreover, through simulations based on two synthetical mobility models and a real-world scenario, we demonstrate the accuracy and correctness of the theoretically obtained result.

The next generation video coding standard HEVC shows high coding performance compared with the H.264/AVC standard, but the computational complexity of the HEVC encoder (HM3.0) is significantly higher. In this letter, the early termination of the CU encoding algorithm is proposed to reduce the computational complexity in the HEVC encoder. The proposed method reduces the encoder complexity by 58.7%, while maintaining the same level of coding efficiency.