A new design methodology is proposed and analyzed for the design of ternary logic systems. In the new ternary logic systems, no conversions among radices are required and only the two-state ternary literals associated with the ternary signals are transmitted in the whole system. With the new design methodology, the ternary systems can be realized by the dynamic CMOS logic circuits which are simple and fully compatible with those of the conventional binary logic circuits in process, power supply, and logic levels. A new dynamic differential logic called the CMOS Redundant Differential Logic (CRDL) is also developed to increase the logic flexibility and the circuit performance. Using the new design methodology and the CRDL circuits, the multiplier with redundant binary addition tree is designed in both non-pipelined and pipelined systems. The experimental chip has been fabricated and measured, which successfully verifies the correctness of the logic functions and the speed performance of the designed circuits.

In many applications involving the processing of noisy signals, it is desired to know the noise variance. This paper proposes a new method for estimating the noise variance from the signals of autoregressive (AR) and autoregressive moving-average (ARMA) systems corrupted by additive white noise. The method proposed here uses the low-order Yule-Walker (LOYW) equations and the lattice filter (LF) algorithm for the estimation of noise variance from the noisy output measurements of AR and ARMA systems, respectively. Two techniques are proposed here: iterative technique and recursive one. The accuracy of the methods depends on SNR levels, more specifically on the inherent accuracy of the Yule-Walker and lattice filter methods for signal plus noise system. The estimated noise variance is used for the blind indentification of AR and ARMA systems. Finally, to demonstrate the effectiveness of the method proposed here many numerical results are presented.

The generation and design of a stationary Markov signal are discussed as an inverse problem, in which one looks for a transition probability when a stationary probability distribution is given. This paper presents a new solution to the inverse problem, which makes it possible to design and generate a Markov random signal with arbitrary probability distribution and an exponential correlation function. Several computer results are illustrated in figures.

Myoelectric (ME) signals during dynamic movement suffer from motion arifact noise caused by mechanical friction between electrodes and the skin. It is difficult to reject artifact noises using linear filters, because the frequency components of the artifact noise include those of ME signals. This paper describes a nonlinear method of eliminating artifacts. It consists of an inverse autoregressive (AR) filter, a nonlinear filter, and an AR filter. To deal with ME signals during dynamic movement, we introduce an adaptive procedure and fuzzy rules that improve the performance of the nonlinear filter for local features. The result is the best ever reported elimination performance. This fuzzy rule based adaptive nonlinear artifact elimination filter will be useful in measurement of ME signals during dynamic movement.

This paper reviews recent progress in adaptive signal processing techniques for digital mobile radio communications. In Radio Signal Processing (RSP) , digital signal processing is becoming more important because it makes it relatively easy to develop sophisticated adaptive processing techniques, Adaptive signal processing is especially important for carrier signal processing in RSP. Its main objective is to realize optimal or near-optimal radio signal transmission. Application environments of adaptive signal processing in mobile radio are clarified. Adaptive equalization is discussed in detail with the focus on adaptive MLSE based on the blind algorithm. Demodulation performance examples obtained by simulations and experiments are introduced, which demonstrates the recent advances in this field. Next, new trends in adaptive array processing, interference cancelling, and orthogonalization processing are reviewed. Finally, the three automatic calibration techniques that are based on adaptive signal processing are described for realizing high precision transmission devices.

In order to realize a continuous-time system model in digital computers, we must construct a discrete-time system model simulating the continuous-time processes in some characteristic aspect. Though many discretization methods have been proposed, they do not necessarily provide a discrete-time system in which input, state and output are identical with the sampled values of the original continuous-time system. The isomorphism discretization that all of the input, state and output of a continuous-time system can be recovered from the corresponding discrete-time system is crucial for our analysis. This paper aims at guaranteeing the isomorphism between a continuous- and a discrete-time system models (fluency system model) which were proposed by the authors. The isomorphism of input space had been already shown in the previous works by one of the authors. In this paper, by showing the isomorphism of the state function and output spaces, the aim will be achieved.

An adaptive method analyzing analytic speech signals is proposed in this paper. The method decreases the errors of finite precision on calculation in a method with real coefficients. It is shown from the results of experiments that the proposed method is more useful than adaptive methods with real coefficients.

Relating to the problem of suppressing the immanent redundancy contained in an image with out vitiating the quality of the resultant approximation, the interpolation of multi-dimensional signal is widely discussed. The minimization of the approximation error is one of the important problems in this field. In this paper, we establish the optimum interpolatory approximation of multi-dimensional orthogonal expansions. The proposed approximation is superior, in some sense, to all the linear and the nonlinear approximations using a wide class of measures of error and the same generalized moments of these signals. Further, in the fields of information processing, we sometimes consider the orthonormal development of an image each coefficient of which represents the principal featurr of the image. The selection of the orthonormal bases becomes important in this problem. The Fisher's criterion is a powerful tool for this class of problems called declustering. In this paper, we will make some remarks to the problem of optimizing the Fisher's criterion under the condition that the quality of the approximation is maintained.

This paper describes the general conditions for perfect signal reconstruction in adaptive blocksize MDCT. MDCT, or modified Discrete Cosine Transform, is a method in which blocks are laid to overlap each other. Because of block overlapping, some consideration must be paid to reconstructing the signals perfectly in adaptive blocksize schemes. The perfect reconstruction conditions are derived by considering the reconstruction signals, on a segment by segment basis. These conditions restrict the analysis/synthesis windows in the MDCT formula. Finally, this paper evaluates two examples of window sets, including windows used in the ISO MPEG audio coding standard.

Fluency approach is to deal with staircase, polygonal and band-limited signals as those in a unified series of signal spaces of which characteristics vary with the parameter of degree. Scaling functions and their duals have been obtained which fulfill a part of the requirements to constitute a multiresolutional analysis in this approach. The purpose of the present paper is to derive general formulae to express wavelets and their duals which fulfill the rest of the requirements. It is the first step to have a general expression of every possible wavelet in selecting a wavelet. The degree is limited to be arbitrary positive oddintegers so far in this paper. The genaral formulae derived in this paper are in the form of linear combinations of the sampling functions, which are scaling functions, and their duals. These formulae can be also regarded as a reduced version of the conditions for multiresolutional analysis in terms of sampling functions and their duals. The general formulae provide a start point for selecting a wavelet which decides characteristics of a multiresolutional analysis in the fluency approach. Some criteria for the concrete selection for each purpose of multiresolutional analysis and a formula for the even-degree cases are yet to be aquired in the future.

Truncated sum (TSUM for short) is useful for MV-PLA's realization. This paper introduces a new class of multiple-valued logic functions that are expressed by truncated sum, differential product (DPRODUCT for short), NOT and variables, where TSUM (x, y)min (xy, p1) and DPRODUCT (x, y)max (xy(p1), 0) is newly defined as the product that is derived by applying De Morgan's laws to TSUM. We call the functions T-functios. First, this paper clarifies that a set of T-functions is not a lattice. It clarifies that Lukasiewicz implication can be expressed by TSUM and NOT. It guarantees that a set of p-valued T-functios is not complete but complete with constants. Next, the speculations of the number of T-functions for less than ten radixes are derived. For eleven or more radix p, a speculation of the number of p-valued T-functions is shown. Moreover, it compares the T-functions with B-functions. The B-functions have been defined as the functions expressed by MAX, MIN, NOT and variables. As a result, it shows that a set of T-functions includes a set of B-functions. Finally, an inclusion relation among these functional sets and normality condition is shown.

Wave digital filters are a class of digital filters. They are equivalent to commensurate transmission line circuits synthesized with uniform, lossless, and commensurated transmission lines. In order to extend their applications to physical wave phenomena including quantum electronics, it is necessary to consider a generalized distributed line whose velocity of energy flow has frequency characteristics. This paper discusses a generalized distributed circuit, and we obtain two types of lines, lossless and cut-off. In order to analyze these lines, we discuss signal flow graphs of steady state voltage and current. The reflection factors we obtain here are the same as that for an active power or a diagonal element of a scattering matrix, which is zero in conjugate matching. By using this reflection factor, we obtain band-pass filters synthesized with the cut-off lines. We also describe an analysis method for nonuniform line related to Riccati differential equation.

In the band-limited signal space, the mutual relation between continuous time signal and discrete time signal is expressed by the sampling theorem of Whittaker-Someya-Shannon. This theorem consists of an orthonormal expansion formula using sinc functions. In that formula, the expansion coefficients are identical to the sample values of signals. In general, the bandlimited signal space is not always suited to model the signals in nature. The authors have proposed a new model for signal processing based on finite times continuously differentiable functions. This paper aims to complete the sampling theorem for the spline signal spaces, which corresponds to the sampling theorem of Whittaker-Someya-Shannon in the band-limited signal space. Since the obtained sampling theorem gives the simplest representation of signals, it is considered to be the most fundamental characterization of spline functions used for signal processing. The biorthonormal basis derived in this paper is considered to be a system of delta functions at sampling points with some continuous differentiability.

This paper describes a 32-bit fully asynchronous microprocessor, with 4-stage pipeline based on a RISC-like architecture. Issues relevant to the processor such as design of self-timed datapath, asynchronous controller and interconnection circuits are discussed. Simulation results are included using parameters extracted from layout, which showed about the 300 MIPS processing speed and used 71,000 transistors with 0.5 µm CMOS technology.

This paper advocates the use of linear objective function in analytic analog placement. The role of linear and quadratic objctive functions in the behavior and results of an analog placement algorithm based on the force directed method is discussed. Experimental results for a MCNC benchmark circuit and another one from text books are shown to demonstrate the effect of a linear and a quadratic objective function on the analog constraint satisfaction and CPU time. By introducing linear objective function to the algorithm, we obtain better placements in terms of analog constraint satisfaction and computation cost than in case of conventional quadratic objective function.

This letter extends the Yule-Walker method to the estimation of ARMA parameters from output measurements corrupted by noise. In the proposed method it is assumed that the noise variance and the input are unknown. An algorithm for the estimation of noise variance is, therefore, given. The use of the variance estimation method proposed here together with the Yule-Walker equations allow the estimation of the parameters of a minimum phase ARMA model based only on noisy measurements of its output. Moreover, using this method it is not necessary to slove a set of nonlinear equations for MA parameter estimation as required in the conventional correlation based methods.

Many previous works state that a multiple Sidelobe canceller (MSLC) with two auxiliary antennas is successful in suppressing two interference signals received simultaneously by sidelobes of a main antenna. In this paper, we show that the MSLC does not always guarantee such capability in three dimensional applications where the incident direction of interference signals is defined by two angles (elevation and azimuth). We show the singularity of the autocorrelation matrix for the auxiliary channel signals induces the degradation of the capability by analyzing characteristics of MSLC's in three dimensional applications from the view point of the eigenvalue problem. To overcome this singularity, we propose a novel MSLC controlling the placement of auxiliary antennas by means of switching over three antennas arranged triangularly. Some simulations are conducted to show the effectiveness of the proposed MSLC.

This paper deals with the wire length expressions using differentiable nonlinear functions, as a result they can be used in analytical placement methods. These expressions can be applicable to clique, bipartite-graph, and half-perimeter net models, and quadratic and Manhattan metrics to estimate the wire lengths.

A C1 interpolation scheme for constructing surface patch on n-sided region (n5, 6) is presented. The constructed surface patch matches the given boundary curves and cross-boundary slopes on the sides of the n-sided region (n5, 6). This scheme has relatively simple construction, and offers one degree of freedom for adjusting interior shape of the constructed interpolation surface. The polynomial precision set of the scheme includes all the polynomials of degree three or less. The experiments for comparing the proposed scheme with two schemes proposed by Gregory and Varady respectively and also shown.

The scope of this paper is the realization of FIR digital filters with an emphasis on linear phase and maximally flat cases. The transfer functions of FIR digital filters are polynomials and polynomial evaluation algorithms can be utilized as realization schemes of these filters. In this paper we investigate the application of a class of polynomial evaluation algorithms called "recursive triangles" to the realization of FIR digital filters. The realization of an arbitrary transfer function using De Casteljau algorithm, a member of the recursive triangles used for evaluating Bernstein polynomials, is studied and it is shown that in some special and important cases it yields efficient modular structures. Realization of two dimensional filters based on Bernstein approximation is also considered. We also introduce recursive triangles for evaluating the power basis representation of polynomials and give a new multiplier-less maximally flat structure based on them. Finally, we generalize the structure further and show that Chebyshev polynomials can also be evaluated by the triangles. This is the triangular counterpart of the well-known Chebyshev structure. In general,the triangular structures yield highly modular digital filters that can be mapped to an array of concurrent processors resulting in high speed and effcient filtering specially for maximally flat transfer functions.