In loudspeaker-based 3D audio systems, there are some acoustic crosstalk cancellation methods to enlarge the 'sweet spot' around a fixed listener position. However, these methods have common defect that most of them can be applied only to the specific narrow frequency band. In this letter, we propose the more robust acoustic crosstalk cancellation method so that we can cancel the crosstalk signal in far wider frequency band and enlarge 'sweet spot. ' For this goal, we apply a sum and difference filter to the conventional three loudspeaker-based 3D audio system.

This letter presents a new approach for obtaining the expected waiting time for packets under the drop-head (also called a drop-from-front) scheme for buffer management. The results show that the drop-head scheme is more effective in reducing queueing delays than the drop-tail scheme.

This letter proposes recursive space-time TCM with two transmit antennas. A recursive component code is crucial in a serial or parallel concatenation scheme. These codes were obtained through computer search and their performance was simulated and compared with previously known codes.

Vector quantization (VQ) is an attractive image compression technique. VQ utilizes the high correlation between neighboring pixels in a block, but disregards the high correlation between the adjacent blocks. Unlike VQ, side-match VQ (SMVQ) exploits codeword information of two encoded adjacent blocks, the upper and left blocks, to encode the current input vector. However, SMVQ is a fixed bit rate compression technique and doesn't make full use of the edge characteristics to predict the input vector. Classified side-match vector quantization (CSMVQ) is an effective image compression technique with low bit rate and relatively high reconstruction quality. It exploits a block classifier to decide which class the input vector belongs to using the variances of neighboring blocks' codewords. As an alternative, this paper proposes three algorithms using gradient values of neighboring blocks' codewords to predict the input block. The first one employs a basic gradient-based classifier that is similar to CSMVQ. To achieve lower bit rates, the second one exploits a refined two-level classifier structure. To reduce the encoding time further, the last one employs a more efficient classifier, in which adaptive class codebooks are defined within a gradient-ordered master codebook according to various prediction results. Experimental results prove the effectiveness of the proposed algorithms.

There are several attempts to generate chaotic binary sequences by using one-dimensional maps. From the standpoint of engineering applications, it is necessary to evaluate statistical properties of sample sequences of finite length. In this paper we attempt to evaluate the statistics of chaotic binary sequences of finite length. The large deviation theory for dynamical systems is useful for investigating this problem.

Deforestation is a well-known program transformation technique which eliminates intermediate data structures that are passed between functions. One of its weaknesses is the inability to deforest programs using accumulating parameters. We show how certain kinds of intermediate lists produced by accumulating parameters can be deforested. In this paper we introduce an accumulative variant of foldr, called rdlof, and show the composition of functions defined by foldr and rdlof. As a simplified instance of foldr and rdlof, we then examine dmap, an accumulative extension of map, and give the corresponding fusion rules. While the associated composition rules cannot capture all deforestation problems, they can handle accumulator fusion of fold- and map-style functions in a simple manner. The rules for accumulator fusion presented here can also be viewed as a restricted composition scheme for attribute grammars, which in turn may help us to bridge the gap between the attribute and functional worlds.

The radar cross section (RCS) of a dielectric-coated cylindrical cavity was measured and the measurements were compared with those calculated according to the iterative physical optics (IPO). The IPO analysis used the equivalent-impedance boundary condition (EIBC) based on transmission-line theory which takes into account the thickness of the coating. It was consequently found that this condition is much more effective than the ordinary-impedance boundary condition based on the intrinsic impedance of the material.

A number of schemes have been proposed for communication using chaos over the past years. Regardless of the exact modulation method used, the transmitted signal must go through a physical channel which undesirably introduces distortion to the signal and adds noise to it. The problem is particularly serious when coherent-based demodulation is used because the necessary process of chaos synchronization is difficult to implement in practice. This paper addresses the channel distortion problem and proposes a technique for channel equalization in chaos-based communication systems. The proposed equalization is realized by a modified recurrent neural network (RNN) incorporating a specific training (equalizing) algorithm. Computer simulations are used to demonstrate the performance of the proposed equalizer in chaos-based communication systems. The Henon map and Chua's circuit are used to generate chaotic signals. It is shown that the proposed RNN-based equalizer outperforms conventional equalizers.

A novel method for the primitive description of the multiprimitive texture is proposed. This method segments a texture by the watershed algorithm into fragments each of which contains one grain. The similar fragments are grouped by the cluster analysis in the feature space whose basis is the morphological size density. Each primitive is extracted as the grain of the central fragment in each cluster.

In this paper we analyze an asymptotic stability of nonlinear singularly perturbed systems and propose a composite control with gain scheduling where the fast controller is the gain scheduled controller and the slow state plays a role of slowly varying parameters in gain scheduling. Specifically, the slow controller is designed by the slow manifold to stabilize the reduced slow system. As a result, the slow manifold of the system is the same as the designed manifold.

ZCZ sets are families of sequences, whose periodic auto/cross-correlation functions have zero correlation zone at the both side of the zero-shift. They can provide approximately synchronized CDMA systems without intra-cell interference for cellular mobile communications. This paper presents ternary ZCZ sets achieving a mathematical bound, and investigates the average interference parameters for the sets in order to evaluate inter-cell interference. It is shown that they can provide AS-CDMA systems with efficiency frequency usage.

This paper investigates the behavior of one-dimensional discrete-time binary cellular neural networks with both the A- and B-templates and gives the necessary and sufficient conditions for the above network to be stable for unspecified fixed boundaries.

A quasi-synchronous (QS) Multi-Carrier time division duplex DS-CDMA is studied for reverse link on multipath indoor environment. Quasi-synchronous DS-CDMA drastically reduces the effect of multiple access interference with several interesting features of time division duplex (TDD) mode for mobile communications. In this paper, we use the time division duplex transmission mode and each user appropriately adjusts its transmission time, through feed back control from the base station, so its signal can arrive at the base station synchronously with the other mobile stations. This paper evaluates the performance of a quasi-synchronous multi-carrier TDD DS-CDMA for reverse link on multipath indoor environment. The performance results are shown with different quasi-synchronous accuracy and power control error values. Orthogonal codes are used for spreading the signals in QS transmission. On the other hand, random codes are used for an asynchronous transmission. From the results, when the performance of asynchronous system is assumed to be a reference, we can see that the constraint of quasi-synchronous accuracy equals 2.3 chips of multi-carrier system at spreading factor 32.

This paper presents a new Reinforcement Learning (RL) method, called "Labeling Q-learning (LQ-learning)," to solve the partially obervable Markov Decision Process (POMDP) problems. Recently, hierarchical RL methods are widely studied. However, they have the drawback that the learning time and memory are exhausted only for keeping the hierarchical structure, though they wouldn't be necessary. On the other hand, our LQ-learning has no hierarchical structure, but adopts a new type of internal memory mechanism. Namely, in the LQ-learning, the agent percepts the current state by pair of observation and its label, and then, the agent can distinguish states, which look as same, but obviously different, more exactly. So to speak, at each step t, we define a new type of perception of its environment õt=(ot,θt), where ot is conventional observation, and θt is the label attached to the observation ot. Then the classical RL-algorithm is used as if the pair (ot,θt) serves as a Markov state. This labeling is carried out by a Boolean variable, called "CHANGE," and a hash-like or mod function, called Labeling Function (LF). In order to demonstrate the efficiency of LQ-learning, we will apply it to "maze problems" in Grid-Worlds, used in many literatures as POMDP simulated environments. By using the LQ-learning, we can solve the maze problems without initial knowledge of environments.

Recently there has been increased attention to the causality among biomedical signals. The causality between brain structures involved in the generation of alpha activity is examined based on EEG signals acquired simultaneously in the frontal and occipital regions of the scalp. The concept of directed coherence (DC) is introduced as a means of resolving two-signal observations into the constituent components of original signals, the interaction between signals and the influence of one signal source on the other, through autoregressive modeling. The technique was applied to EEG recorded from 11 normal subjects with eyes closed. Through an analysis of the directed coherence, it was found that in both the left and right hemispheres, alpha rhythms with relatively low frequency had a significantly higher correlation in the frontal-occipital direction than in the opposite direction. In the upper alpha frequency band, a significantly higher DC was observed in the occipital-frontal direction, and the right-left DC in the occipital area was consistently higher. The activity of rhythms near 10 Hz was widespread. These results suggest that there is a difference in the genesis and the structure of information transmission in the lower and upper band, and for 10-Hz alpha waves.

This paper introduces an improved multistage parallel interference cancellation (PIC) technique that uses the reverse-link synchronous transmission technique (RLSTT) to improve the estimation of data at the initial stage. Because the subtraction of an interfering signal based on an incorrect bit decision quadruples the interference power for that signal, the relatively high decision bit error rate (BER) may lead to a poor cancellation or even a higher BER at the following stages. The RLSTT is a robust approach which takes into account the fact the tentative decision at the earlier stages is less reliable than the following stages and makes the earlier cancellation more reliable. The analysis demonstrates that a better transmission performance can be achieved by using the RLSTT at the initial stage of PIC.

In this letter we present a new way for computing generalized eigenvalue problems in engineering applications. To transform a generalized eigenvalue problem into an associated problem for solving nonlinear dynamic equations by using optimization techniques, we can determine all eigenvalues and their eigenvectors for general complex matrices. Numerical examples are given to verify the formula of dynamic equations.

For base station antenna array systems with time-division-duplex (TDD) mode, downlink channel responses are equal to uplink channel responses if the duplexing time is small, thus it is often believed that TDD mode simplies downlink beamforming problem as uplink weights can be applied for downlink directly. In this letter, we show that for TDD DS-CDMA systems, even though uplink and downlink channel responses are equal, optimal uplink weights are no longer equal to the optimal downlink ones due to asynchronous property in uplink and synchronous property in downlink, as well as different data rate traffic and QoS requirements. Computer simulations show that for asymmetric traffic, if uplink weights are used for downlink directly, downlink system capacity is less than 50% of that with optimal downlink weights.

In this paper, a novel continuous complementary sliding control was proposed to improve the tracking performance given the available control bandwidth and the extend of parameter uncertainty. With this control law, the ultimate bound of tracking error was shown to be reduced at least by half, as compared with the conventional continuous sliding control. More strikingly, the proposed control can effectively improve the error transient response during the reaching phase. We presented a composite complementary sliding control scheme for a class of uncertain nonlinear systems including the nonlinear electrohydraulic position servo control system, which will be used as an illustrated example. Simulation results indicated exceptional good tracking performance to step and sine wave reference inputs can be obtained. In addition, the disturbance rejection property of the controller to single-frequency sinusoidal disturbances is also outstanding.

In this paper, a new voice personality transformation algorithm which uses the vocal tract characteristics and pitch period as feature parameters is proposed. The vocal tract transfer function is divided into time-invariant and time-varying parts. Conversion rules for the time-varying part are constructed by the classified-linear transformation matrix based on soft-clustering techniques for LPC cepstrum expressed in KL (Karhunen-Loève) coefficients. An excitation signal containing prosodic information is transformed by average pitch ratio. In order to improve the naturalness, transformation on the excitation signal is separately applied to voiced and unvoiced bands to preserve the overall spectral structure. Objective tests show that the distance between the LPC cepstrum of a target speaker and that of the speech synthesized using the proposed method is reduced by about 70% compared with the distance between the target speaker's LPC cepstrum and the source speaker's. Also, subjective listening tests show that 60-70% of listeners identify the transformed speech as the target speaker's.