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.

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.

In this paper we treat a novel adaptation strength according to neighborhood ranking of self-organizing neural networks with the objective of avoiding the initial dependency of reference vectors, which is related to the strength in the neural-gas network suggested by Martinetz et al. The present approach exhibits the effectiveness in the average distortion compared to the conventional technique through numerical experiments. Furthermore the present approach is applied to image data and the validity in employing as an image coding system is examined.

In previous work we have proposed a steganographic technique for gray scale images called BPCS-Steganography. We also apply this technique to full color images by decomposing the image into its three color component images and treating each as a gray scale image. This paper proposes a method to apply BPCS-Steganography to palette-based images. In palette-based images, the image data can be decomposed into color component images similar to those of full color images. We can then embed into one or more of the color component images. However, even if only one of the color component images is used for embedding, the number of colors in the palette after embedding can be over the maximum number allowed. In order to represent the image data in palette-based format, color quantization is therefore needed. We cannot change the pixel values of the color component image that contains the embedded information, but can only change the pixel values of the other color component images. We assume that the degrading of the color component2 image with information embedded is smaller than that of the color component images that are used for color reduction. We therefore embed secret information into the G component image, because the human visual system is more sensitive to changes the luminance of a color, and G has the largest contribution to luminance of the three color components. In order to reduce the number of colors, the R and B component images are then changed in a way that minimizes the square error.

In this work we study the performance of a distributed GA that incorporates in its core parallel cooperative-competitive genetic operators. A series of controlled experiments are conducted using various large and difficult 0/1 multiple knapsack problems to test the robustness of the distributed GA. Simulation results verify that the proposed distributed GA compared with a canonical distributed GA significantly gains in search speed and convergence reliability with less communication cost for migration.

Let us introduce n ( 2) mappings fi (i=1,2,,n) defined on complete linear metric spaces (Xi-1, ρ) (i=1,2,,n), respectively, and let fi:Xi-1 Xi be completely continuous on bounded convex closed subsets Xi-1(0) Xi-1, (i=1,2,,n 0), such that fi(Xi-1(0)) Xi(0). Moreover, let us introduce n set-valued mappings Fi : Xi-1 Xi (Xi)(the family of all non-empty closed compact subsets of Xi), (i=1,2,,n 0). Here, we have a fixed point theorem on the successively recurrent system of set-valued mapping equations: xi Fi(xi-1, fi(xi-1)), (i=1,2,,n 0). This theorem can be applied immediately to analysis of the availability of system of circular networks of channels undergone by uncertain fluctuations and to evaluation of the tolerability of behaviors of those systems. In this paper, mathematical situation and detailed proof are discussed, about this theorem.

Microstrip antennas with meshed ground planes are suitable for radiation elements of large satellite phased array antennas. Although they have some mechanical advantages such as the possibility of antenna weight reduction, they also cause electrical problems such as the resonant frequency shift and F/B ratio degradation. The first purpose of this paper is the analytical understanding of the resonant frequency shift, for which two perturbational methods are proposed. One has a closed form expression that provides some useful design data. The other is to solve the integral equations by using the periodicity of the meshed ground plane, which gives more accurate results. The second purpose of this paper is to investigate the backward radiation from the meshed ground plane analytically, for which we derive an analysis method from the calculated results of the resonant frequency shift. The proposed methods are verified with the measured ones.

The paper deals with the estimation method of system equations of dynamic behavior of an input-pricing mechanism by using the Genetic Programming (GP) and its applications. The scheme is similar to recent noise reduction method in noisy speech which is based on the adaptive digital signal processing for system identification and subtraction estimated noise. We consider the dynamic behavior of an input-pricing mechanism for a service facility in which heterogeneous self-optimizing customers base their future join/balk decisions on their previous experiences of congestion. In the GP, the system equations are represented by parse trees and the performance (fitness) of each individual is defined as the inversion of the root mean square error between the observed data and the output of the system equation. By selecting a pair of individuals having higher fitness, the crossover operation is applied to generate new individuals. The string used for the GP is extended to treat the rational form of system functions. The condition for the Li-Yorke chaos is exploited to ensure the chaoticity of the approximated functions. In our control, since the system equations are estimated, we only need to change the input incrementally so that the system moves to the stable region. By assuming the targeted dynamic system f(x(t)) with input u(t)=0 is estimated by using the GP (denoted (x(t))), then we impose the input u(t) so that xf= (t+1)=(x(t))+u(t) where xf is the fixed point. Then, the next state x(t+1) of targeted dynamic system f(x(t)) is replaced by x(t+1)+u(t). We extend ordinary control method based on the GP by imposing the input u(t) so that the deviation from the targeted level xL becomes small enough after the control. The approximation and control method are applied to the chaotic dynamics generating various time series based on several queuing models and real world data. Using the GP, the control of chaos is straightforward, and we show some example of stabilizing the price expectation in the service queue.

Active integrated antennas are a maturing topic. Many novel configurations have been described and system designers are how investigating how the advantages of compactness and increased functionality can be exploited in applications. In this paper, the various types of integrated antennas are discussed together with possible ways of exploiting the technology. New configurations of direct conversion integrated antennas are then described in detail, which illustrate some of the possibilities inherent in the technology.

In this letter, we introduce a two-state turbo-TCM scheme based on the concatenated tree codes. The proposed scheme can achieve near capacity performance yet has considerably lower decoding complexity compared with other existing turbo-TCM codes.

We have demonstrated synchronization of chaos in a pair of one-way coupled Colpitts oscillators by both experiment and numerical simulation. We have investigated parameter regions for achieving chaos-synchronization when one of the internal parameters is mismatched between the master and slave oscillators, and clarify the tolerance of parameter regions for synchronization against parameter mismatching.

This paper proposes a novel packet classification method using ternary content-addressable memory (TCAM), which can store very wide policy rules despite the limited width of TCAM. For IP version 6, policy rules could be 304 bits wide. This method enables us to use commercially available TCAM for packet classification and thus builds an ultra high-speed policy based packet forwarding engine for differentiated services on the Internet.

The Belousov-Zhabotinsky (BZ) reaction provides us important clues in controlling 2D phase-lagged stable synchronous patterns in an excitable medium. Because of the difficulty in computing reaction-diffusion systems in large systems using conventional digital processors, we here propose a cellular-automaton (CA) circuit that emulates the BZ reaction. In the circuit, a two-dimensional array of parallel processing cells is responsible for fast emulation, and its operation rate is independent of the system size. The operations of the proposed CA circuit were demonstrated by using a simulation program with integrated circuit emphasis (SPICE).

The cooperative and competitive network suitable for circuit realization is presented, based on the network proposed by Amari and Arbib. To ensure WTA process, the output function of the original network is replaced with the piecewise linear function and supplying the inputs as pulse waveforms is obtained. In the SPICE simulations, it is confirmed that the network constructed by operational amplifiers attains WTA process, even if the scale of the network becomes large.

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.

The lossy magnetic composite material made from soft magnetic metal powder and rubber is widely used as an EMI countermeasure material, due to its higher magnetic loss than those of spinel ferrites in microwave frequencies. In this paper, we clarify the material characteristics by measuring the relative complex permeability r and relative complex permittivity r of two kinds of composite materials in microwave frequencies. Since the composite materials are anisotropic, both r and r are measured as diagonal tensors by utilizing extended S-parameter method. The results show that the imaginary part of r of flaky-powder composite exceeded the Snoek's limit for the spinel ferrites which has been reported so far. The measured r and r are partially compared with those measured by cavity resonator method, and good agreement is obtained.

Location management is crucial for mobile systems. A mobile must be located whenever a connection is established. Thus, mobile systems must cope with frequent location updates and queries. In addition to the HLR/VLR scheme in IS-41 and GSM, the feasibility of reducing the network load caused by locating mobile users has received considerable attention. One user location algorithm called "Pointer Forwarding with Single HLR," was proposed to reduce location update cost. Thereafter, the distributed HLR scheme was proposed to prevent HLR from becoming a signal bottleneck in the signaling network. This approach eliminates the cost of updating multiple HLRs, vastly reducing the database access delay, but also introduces long pointer chain traverse that may cause large location tracking costs and long call delivery times/costs. This study proposes a efficient location tracking strategy, named, "Fast Pointer Forwarding Strategy with Distributed HLR. " This strategy ensures that the pointer chain length never exceeds one. In fact, this strategy provides an upper bound on location tracking time. Its performance is numerically analyzed. Results in this study demonstrate that our strategy can considerably reduce the complexity of implementation and the call delivery time/cost.

In this paper, a high performance 3232-bit multiplier for a DSP core is proposed. The multiplier is composed of a block of Booth Encoder, a block of data compression, and a block of a 64-bit adder. In the block of Booth encoder, a conditional sign decision Booth encoder that reduces the gate delay and power consumption is proposed. In the block of data compression, 4-2 and 9-2 data compressors based on a novel compound logic are used for the efficient compressing of extra sign bit. In the block of 64-bit adder, an adaptive MUX-based conditional select adder with a separated carry generation block is proposed. The proposed 3232-bit multiplier is designed by a full-custom method and there are about 28,000 transistors in an active area of 900 µm 500 µm with 0.25 µm CMOS technology. From the experimental results, the multiplication time of the multiplier is about 3.2 ns at 2.5 V power supply, and it consumes about 50 mW at 100 MHz.

The starting point of this paper is the definition of a nonlinear model of the read out process in high density optical discs. Under high density condition, the signal read out is not a linear process, and suffers also from cross talk. To cope with these problems, the identification of a suitable nonlinear model is required. A physical model based on the optical scalar theory is used to identify the kernels of a nonlinear model based on the Volterra series. Both analysis and simulations show that a second order bidimensional model accurately describes the read out process. Once equipped with the Volterra channel model, we evaluate the performance of various nonlinear receivers. First we consider Nonlinear Adaptive Volterra Equalization (NAVE). Simulations show that the performance of classical structures for linear channels is significantly affected by the nonlinear response. The nonlinear NAVE receiver can achieve better performance than Maximum Likelihood Sequence Estimator (MLSE), with lower complexity. An innovative Nonlinear Maximum Likelihood Sequence Estimator (NMLSE), based on the combination of MLSE and nonlinear Inter-Symbol Interference (ISI) cancellation, is presented. NMLSE offers significant advantages with respect to traditional MLSE, and performs better than traditional equalization for nonlinear channels (like NAVE). Finally, the paper deals with cancellation of cross talk from adjacent tracks. We propose and analyze an adaptive nonlinear cross talk canceller based on a three spot detection system. For the sake of simplicity, all the performance comparisons presented in this paper are based on the assumption that noise is Additive, White, and Gaussian (AWGN model).

In this paper, we focus on an image encryption scheme based on a truncated Baker transformation. The truncated Baker transformation globally preserves the original dynamics of Baker transformation but incorporates a random local rotation operator between two neighbor elements in the mapping domain in order to keep a finite precision. It generates binary sequences (the dynamics of elements) which have statistically good features on ergodicity, mixing and chaotic properties. The image encryption scheme extended from the truncated Baker transformation efficiently shuffles the input gray level image satisfying fundamental conditions on confusion and diffusion required for image encryption schemes. However, this scheme uses many binary sequences and thus needs to keep a large volume of secret keys. In order to solve this problem we introduce Peano space-filling curve in this scheme, which remarkably reduce the key size and mapping iterations without deteriorating good shuffling properties attained by this scheme.