This paper introduces a new acoustic-coupling level (ACL) estimation method for an echo reduction based on Wiener filtering. This method employs two techniques: 1) a fast and robust ACL estimation using a short-time correlation between received and microphone input signals in time and frequency spectral domains and 2) compensation of the ACL estimation error caused by the inaccurate correlation obtained when applying the fast Fourier transform (FFT) with a short finite frame length. The proposed ACL estimation method continuously updates the estimated ACL and immediately tracks a rapid echo-path change even during double-talk periods. The performance with this method is demonstrated by simulation results in which the better acoustic-coupling level is obtained than the conventional method, the undesired echo is sufficiently suppressed, and the speech distortion is decreased.

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In this paper, we present a robust and low complexity channel estimation method for a 2×1 multiple input-single output (MISO) digital video broadcasting terrestrial 2 (DVB-T2) system in high speed mobile environments. A two-dimensional (2D) filter with a non-rectangular magnitude response is employed as an interpolation filter in this research work. In order to improve performance of the interpolation filter in a 2×1 MISO system, we propose a 3-point diagonal averaging method. Simulation results show that a combination between the proposed method and the two-stages implementations of a non-rectangular 2D filter produces the best performance in very high speed mobile environments. The proposed method also has a capability to optimize a diversity gain provided by Alamouti scheme.

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In this paper we propose a novel method of model reduction with a time delay for single-input, single-output continuous-time systems by a separable least-squares (LS) approach. The reduced-order model is determined by minimizing the integral of the magnitude squared of the transfer function error. The denominator parameters and time delay of the reduced-order model are represented by the positions of the food sources of the employed bees and searched for by the artificial bee colony algorithm, while the numerator parameters are estimated by the linear LS method for each candidate of the denominator parameters and time delay. All the best parameters and the time delay of the reduced-order model are obtained through the search by the employed, onlooker and scout bees. Simulation results show that the accuracy of the proposed method is superior to that of the genetic algorithm (GA)-based model reduction algorithm.

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In this paper, we propose a cooperative control system with obstacle avoidance for multiple mobile robots using particle swarm optimization (PSO) in an unknown environment to perform tasks that are difficult for a single robot to accomplish. The problem considered in this paper is the exploration of an unknown environment with the goal of finding and tracking targets using multiple mobile robots. The mobile robots only have basic information about the position of other mobile robots and the relative distances between mobile robots and target. PSO has been demonstrated to be a useful algorithm for tracking target applications for multiple mobile robots in unknown environments. The experimental results demonstrate the validity of the proposed cooperative control system with obstacle avoidance of multiple mobile robots that track targets.

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Voltage and current of electricity or electro-magnetic wave are presented by complex functions. Since product of voltage and current represents power, power is presented by complex function. Real part of power presents energy, and imaginary part of power presents reactive power. Eigen oscillation is caused by reactive power. It is well known that unit element of distributed constant circuit has eigen oscillation. LC ladder circuit also has eigen oscillation. This paper shows the condition of a cascade matrix of the circuit having eigen oscillation.

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