This paper presents a digital reaction-diffusion system (DRDS)--a model of a discrete-time discrete-space reaction-diffusion dynamical system--for designing new image processing algorithms inspired by biological pattern formation phenomena. The original idea is based on the Turing's model of pattern formation which is widely known in mathematical biology. We first show that the Turing's morphogenesis can be understood by analyzing the pattern forming property of the DRDS within the framework of multidimensional digital signal processing theory. This paper also describes the design of an adaptive DRDS for image processing tasks, such as enhancement and restoration of fingerprint images.

For low-complexity linear-phase FIR digital filters which have coefficients expressed as canonic signed digit (CSD) code, a design method to impose power-of-two DC gain is proposed. Output signal level can easily be compensated to that of input so that cascading many stages do not cause any gain errors, which are harmful in, for example, high precision measurement systems. The design is formulated as an optimization problem with magnitude response constraints. The integer linear programming modified for CSD codes is solved by the branch and bound method. The design example shows the effectiveness of the obtained filter in comparison with existing CSD filters. Also, an evaluation method for the area to implement the filter into field programmable gate array (FPGA) is proposed. The implementation example shows that the minimum critical path is obtained with only a little increase in the die area.

Explicit formulas for the tap-coefficients of Taylor series based type III FIR digital differentiators have already been presented. However, those formulas were not derived mathematically from the Taylor series and were based on observation of different sets of the results. In this paper, we provide a mathematical proof of the formulas by deriving them mathematically from the Taylor series.

New designs of MAXFLAT discrete and differentiating Hilbert transformers are presented using their interrelationships with digital differentiators. The new designs have the explicit formulas for their tap-coefficients, which are further modified to obtain a new class of narrow transition band filters, with a performance comparable to the Chebyshev filters.

New explicit formulas for tap-coefficients of halfband low/high pass MAXFLAT non-recursive filters are presented by using their relationship with already presented maximally linear type IV differentiators. These formulas are modified to give a new class of narrow transition band filters, with a performance comparable to that of optimal filters.

This paper proposes a private communication system with chaos using fixed-point digital computation. When fixed-point computation is adopted, chaotic properties of the modulated signal should be checked carefully as well as calculation error problems (especially, overflow problems). In this paper, we propose a novel chaos modem system for private communications including a chaotic neuron type nonlinearity, an unstable digital filter and an overflow function. We demonstrate that the modulated signal reveals hyperchaotic property within 10,000 data point fixed-point computation, and evaluate the security of this system in view of the sensitivity of coefficients for demodulation.

A 24-bit, 96 kHz stereo A/D converter (ADC) for DVD-audio has been developed. The single-chip integrates stereo delta-sigma modulators (Δ ΣM's), a voltage reference, and a decimation filter. A fourth-order cascaded Δ ΣM using a local feedback technique was employed to avoid overload without sacrificing noise performance. Low power switched-capacitor techniques were used for implementation. A two-stage decimation filter architecture that reduces digital switching noise was also developed. A merged multi-stage comb filter was used for the first stage, and a bit-serial finite-impulse-response (FIR) filter was used for the second stage. The 18.0 mm2 chip was fabricated in 0.6-µm CMOS with low threshold devices. Measured results show 117 dB A-weighted dynamic range in the 20 kHz passband, with 470 mW power dissipation at 5 V operation.

The VSOP terminal is a new data-acquisition system for the Very-Long-Baseline Interferometry (VLBI). This terminal was primarily designed for ground telescopes in the VLBI Space Observatory Programme (VSOP). New technologies; higher-order sampling and digital filtering techniques, were introduced in the development. A cassette cart was also introduced, which supports 24-hour unattended operations at the maximum data rate of 256 Mbps. The higher-order sampling and digital filtering techniques achieve flat and constant phase response over bandwidth of 32 MHz without using expensive wide base-band converters. The digital filtering technique also enables a variety of observing modes defined on the VSOP terminal, even with a fixed sampling frequency in an A/D converter. The new terminals are installed at Nobeyama, Kashima, Usuda, Mizusawa, and Kagoshima radio observatories in Japan, and are being used in VSOP and other domestic VLBI observations. In this paper the key features of the VSOP terminal focusing on these advanced technologies are presented, and the results of performance tests are shown.

This paper deals with a method of estimating the parameters and the order of a linear system using differential digital filters and the resultant. From the observed signals of the input and output of an objective system, we extract the differential signals from the zero order to an appropriate high order with the same phase characteristics, using several digital filters. On the assumption that the system order is known, we estimate the parameters of the transfer function and evaluate the estimation error bounds. We propose a criterion function generated by the product of the highest order coefficients and the resultant of the numerator and denominator of the estimated transfer function. Applying this criterion function, we can estimate the order of the objective system. The threshold corresponding to this criterion function is evaluated from the deviation in the frequency characteristics of the used differential filters and the error bound of the estimated parameters. In order to demonstrate the propriety of the proposed method, some numerical simulations are presented.

Classification of the new and used bills using the spectral patterns of raw time-series acoustic data (observation data) poses some difficulty. This is the fact that the observation data include not only a bill sound, but also some motor sound and noise by a transaction machine. We have already reported the method using adaptive digital filters (ADFs) to eliminate the motor sound and noise. In this paper, we propose an advanced technique to eliminate it by the neural networks (NNs). Only a bill sound is extracted from observation data using prediction ability of the NNs. Classification processing of the new and used bills is performed by using the spectral data obtained from the result of the ADFs and the NNs. Effectiveness of the proposed method using the NNs is illustrated in comparison with former results using ADFs.

A pipelined architecture is proposed for the normalized least mean square (NLMS) adaptive digital filter (ADF). Pipelined implementation of the NLMS has not yet been proposed. The proposed architecture is the first attempt to implement the NLMS ADF in the pipelined fashion. The architecture is based on an equivalent expression of the NLMS derived in this study. It is shown that the proposed architecture achieves a constant and a short critical path without producing output latency. In addition, it retains the advantage of the NLMS, i. e. , that the step size that assures the convergence is determined automatically. Computer simulation results that confirm that the proposed architecture achieves convergence characteristics identical to those of the NLMS.

Digital Signal Processors with complex arithmetic capability (DSP-C) are useful for various applications. In this paper, we propose a method for the effective implementation of specific circuits with real coefficients on DSP-C. DSP-C has special hardware such as a complex multiplier so that a complex calculation can be performed with only one instruction. First, we show that nodes with two real coefficient input branches can be implemented by complex multiplications. We apply this implementation to 2D circuits and transversal circuits with real coefficients. Next, we introduce a new computational mode (Advanced mode) and a new multiplier into PSI, a kind of DSP-C which has been proposed already, in order to process the circuits effectively. The effectiveness of the proposed method is shown by simulation in the last part.

In this paper, we propose two new pipelined adaptive digital filter architectures. The architectures are based on an equivalent expression of the least mean square (LMS) algorithm. It is shown that one of the proposed architectures achieves the minimum output latency, or zero without affecting the convergence characteristics. We also show that, by increasing the output latency be one, the other architecture can be obtained which has a shorter critical path.

The authors have proposed a design method for two-dimensional (2-D) separable-denominator (SD) periodically time-variant digital filters (PTV DFs) and confirmed their superiority over 2-D time-invariant DFs. In that result, the periodicity matrix representing the periodicity of the varying filter coefficients is, however, restricted to two cases. This paper extends that idea so that the input-output relation of 2-D SD PTV DFs with an arbitrary periodicity matrix can be determined. This enables us to design wide range of 2-D PTV DFs.

This paper deals with a set of differential operators for calculating the differentials of an observed signal by the Daubechies wavelet and its application for the estimation of the transfer function of a linear system by using non-stationary step-like signals. The differential operators are constructed by iterative projections of the differential of the scaling function for a multiresolution analysis into a dilation subspace. By the proposed differential operators we can extract the arbitrary order differentials of a signal. We propose a set of identifiable filters constructed by the sum of multiple filters with the first order lag characteristics. Using the above differentials and the identifiable filters we propose an identification method for the transfer function of a linear system. In order to ensure the appropriateness and effectiveness of the proposed method some numerical simulations are presented.

In this paper a new general method for approximation of arbitrary multiband filter loss specifications, including all classical, maximally flat and equiripple approximations as special cases, is proposed. It is possible to specify different magnitude behavior (flat or equiripple of given degree) and different maximal losses in the different passbands and to optimize all transmission and attenuation zeroes positions or to have some of them fixed. The optimization procedures for adjustment of the filter response are based on modified Remez algorithm and are performed in s-domain what is regarded since recently as an advantage in the case of design of parallel allpass structures based IIR digital filters. A powerful algorithm and appropriate software are developed following the method and their efficiency is verified through design examples.

In this paper, we consider the selection of analysis filters used in the delayless subband adaptive digital filter (SBADF) and propose to use simple analysis filters to reduce the computational complexity. The coefficients of filters are determined using the components of the first order Hadamard matrix. Because coefficients of Hadamard matrix are either 1 or -1, we can analyze signals without multiplication. Moreover, the conditions for convergence of the proposed method is considered. It is shown by computer simulations that the proposed method can converge to the Wiener filter.

FIR digital filters composed of parallel multiple subfilters are proposed. A binary expression of an input signal is decomposed into multiple shorter words, which drive the subfilters having different length. The output error is evaluated by mean squared and maximum spectra. A fast algorithm is also proposed to determine optimal filter lengths and coefficients of subfilters. Many examples confirm that the proposed filters generate smaller output errors than conventional filters under the condition of specified number of multiplications and additions in filter operations. Further, multiplier and adder structures (MAS) to perform the operations of the proposed filters are also presented. The number of gates used in the proposed MAS and its critical path are estimated. The effectiveness of the proposed MAS is confirmed.

In this paper, we compare the performance of evolutionary digital filters (EDFs) for IIR adaptive digital filters (ADFs) in terms of convergence behavior and stability, and discuss their advantages. The authors have already proposed the EDF which is controlled by adaptive algorithm based on the evolutionary strategies of living things. This adaptive algorithm of the EDF controls and changes the coefficients of inner digital filters using the cloning method or the mating method. Thus, the adaptive algorithm of the EDF is of a non-gradient and multi-point search type. Numerical examples are given to demonstrate the effectiveness and features of the EDF such that (1) they can work as adaptive filters as expected, (2) they can adopt various error functions such as the mean square error, the absolute sum error, and the maximum error functions, and (3) the EDF using IIR filters (IIR-EDF) has a higher convergence rate and smaller adaptation noise than the LMS adaptive digital filter (LMS-ADF) and the adaptive digital filter based on the simple genetic algorithm (SGA-ADF) on a multiple-peak surface.

We present a finite-difference time-domain (FD-TD) method with the perfectly matched layers (PMLs) absorbing boundary condition (ABC) based on the multidimensional wave digital filters (MD-WDFs) for discrete-time modelling of Maxwell's equations and show its effectiveness. First we propose modified forms of the Maxwell's equations in the PMLs and its MD-WDFs' representation by using the current-controlled voltage sources. In order to estimate the lower bound of numerical errors which come from the discretization of the Maxwell's equations, we examine the numerical dispersion relation and show the advantage of the FD-TD method based on the MD-WDFs over the Yee algorithm. Simultaneously, we estimate numerical errors in practical problems as a function of grid cell size and show that the MD-WDFs can obtain highly accurate numerical solutions in comparison with the Yee algorithm. Then we analyze several typical dielectric optical waveguide problems such as the tapered waveguide and the grating filter, and confirm that the FD-TD method based on the MD-WDFs can also treat radiation and reflection phenomena, which commonly done using the Yee algorithm.