This paper proposes a novel CMOS analog multiplier. As its significant merit, it is free from mobility reduction and body effect. Thus, the proposed multiplier is expected to have good linearity, comparing with conventional multipliers. Four transistors operating in the linear region constitute the input cell of the multiplier. Their sources and backgates are connected to the ground to cancel the body effect. eTheir gates are fixed to the same bias voltage to remove the effect of the mobility reduction. Input signals are applied to the drains of the input cell transistors through modified nullors. The simulation results show that THD is less than 0.8% for 0.6 V p-p input signal at 2.5-V supply voltage, and that the 3-dB bandwidth is up to about 13.3 MHz.

In this work, we propose an End-to-End Rate Control Approach (EERCA) for congestion avoidance in Available Bit Rate (ABR) service on Asynchronous Transmit Mode (ATM) networks. In our approach, the network estimates the number of cells stored in the switch for each VC. The source generates a specific traffic pattern, then a proper explicit rate can be derived based on the received traffic pattern at the destination. This approach is designed to reduce the rate calculation effort in the switch as well as to avoid the complexity in setting the monitoring-interval. EERCA features higher efficiency, higher utilization, more stable queue occupancy, shorter transient response time, and better fairness compared with existed schemes.

The development of saturation diving in civil and defense applications has enabled man to work in the sea at great depths and for long periods of time. This advance has resulted, in part, as a consequence of the substitution of helium for nitrogen in breathing gas mixtures. However, utilization of HeO2 breathing mixture at high ambient pressures has caused problems in speech communication; in turn, helium speech enhancement systems have been developed to improve diver communication. These speech unscramblers attempt to process variously the grossly unintelligible speech resulting from the effect of breathing mixtures and ambient pressure, and to reconstruct such signals in order to provide adequate voice communication. It is known that the glottal excitation is quasi-periodic and the vocal tract filter is quasi-stationary. Hence, it is possible to use an auto regressive modelisation to restore speech intelligibility in hyperbaric conditions. Corrections are made on the vocal tract transfer function, either in the frequency domain, or directly on the autocorrelation function. A spectral subtraction or noise reduction may be added to improve speech quality. A new VAD enhanced helium speech unscrambler is proposed for use in adverse conditions or in speech recognition. This system, implementable on single chip DSP of current technology, is capable to work in real time.

In this paper, we propose a new denoising algorithm based on the dyadic wavelet transform (DWT) for ECG signals corrupted with different types of synthesized noise. Using the property that DWT is overcomplete, we define some convex sets in the set of wavelet coefficients and give an iterative method of the projection on the convex sets. The results show that the noises are not only removed from ECG signals, but also the ECG signals are reconstructed, which is used in detecting QRS complex. The performance of the proposed algorithm is demonstrated by some experiments in comparison with the conventional methods.

This paper proposes a fast scheduling algorithm based on gradual time-frame reduction for datapath synthesis of digital signal processing hardwares. The objective of the algorithm is to minimize the costs for functional units and registers and to maximize connectivity under given computation time and initiation interval. Incorporating the connectivity in a scheduling stage can reduce multiplexer counts in resource binding. The algorithm maximizes connectivity with maintaining low time complexity and obtains datapath designs with totally small hardware costs in the high-level synthesis environment. The algorithm also resolves inter-iteration data dependencies and thus realizes pipelined datapaths. The experimental results demonstrate that the proposed algorithm reduces the multiplexer counts after resource binding with maintaining low costs for functional units and registers compared with eight conventional schedulers.

This paper presents two kinds of simplification methods for incompletely specified sequential machines. The strategy of the methods is that as many states in original machines are covered in the simplification processes as possible. The purpose of the methods is to derive a simplified machine having either the largest maximal compatible set or its subset. With the methods, one of the minimal machines can not be always derived, but a near-minimal machine can be obtained more quickly with less memory, since they need not derive all the compatible sets. In this paper, the effectiveness of the methods is checked by applying them to simplification problems of incompletely specified machines generated by using random numbers, and of the MCNC benchmark machines. The experimental results show that our methods can derive a simplified machine quickly, especially for machines having a great number of states or don't care rate.

Huet and Levy showed that index reduction is a normalizing strategy for every orthogonal strongly sequential term rewriting system. Toyama extended this result to root balanced joinable strongly sequential systems. In this paper, we present a class including all root balanced joinable strongly sequential systems and show that index reduction is normalizing for this class. We also propose a class of left-linear (possibly overlapping) NV-sequential systems having a normalizing strategy.

This paper studies the ambiguity reduction ability of a probabilistic context-free grammar. We theoretically analyze a common behavior of any probabilistic context-free grammar. Moreover, we confirm by experiments that a probabilistic context-free grammar learnt from Japanese corpus has the ambiguity reduction ability as expected by the theoretical analysis.

In this paper, three issues concerning the linear adaptive receiver using the LMS algorithm for single-user demodulation in direct-sequence/code-division multiple-access (DS/CDMA) systems are considered. First, the convergence rate of the LMS algorithm in DS/CDMA environment is considered theoretically. Both upper and lower bounds of the eigenvalue spread of the autocorrelation matrix of receiver input signals are derived. It is cleared from the results that the convergence rate of the LMS algorithm becomes slow when the signal power of interferer is large. Second, fast converging technique using a prefilter is considered. The LMS based adaptive receiver using an adaptive prefilter adjusted by a Hebbian learning algorithm to decorrelate the input signals is proposed. Computer simulation results show that the proposed receiver provides faster convergence than the LMS based receiver. Third, the complexity reduction of the proposed receiver by prefiltering is considered. As for the reduced complexity receiver, it is shown that the performance degradation is little as compared with the full complexity receiver.

From the standpoint of reducing the electromagnetic (EM) absorption in the human head for portable telephones, a ferrite sheet is proposed to use as a protection attachment between the antenna and the head. By using an anatomically based head model and a realistic portable telephone model, the effects of the ferrite sheet on both the reduction of EM absorption and antenna radiation pattern are numerically analyzed by the finite-difference time-domain (FDTD) method. The results show that a ferrite sheet can result in a reduction over 13% for the spatial peak SAR averaged over one gram of tissue relative to a degradation below 0.6 dB for the antenna radiation pattern.

This paper proposes a heuristic algorithm for state minimization of incompletely specified finite state machines (FSMs). The strategy is similar to that in ESPRESSO, a wellknown heuristic algorithm for two-level logic minimization. It consists of generating an initial solution, the set of maximal compatibles, and attempting to apply a series of transformations to the solution. The main transformation is to reduce each compatible in the solution and delete unnecessary compatibles by iterative improvements. Other transformations, such as expansion and merging of compatibles, are also introduced for further reduction. When the number of compatibles is likely to be too large to handle explicitly, they are represented by a Binary Decision Diagram. Experimental results show that the proposed method finds better solutions in shorter CPU times for most of the examples than conventional methods.

Let L be any class of languages, L' be one of the classes of context-free, context-sensitive and recursively enumerable languages, and Σ be any alphabet. In this paper, we show that if the following statement (1) holds, then the statement (2) holds. (1) For any language L in L over Σ, there exist an alphabet Γ including Σ, a homomorphism h:Γ*Σ* defined by h(a)=a for aΣ and h(a)=λ (empty word) for aΓ-Σ, a Dyck language D over Γ, and a language L1 in L' over Γ such that L=h(DL1). (2) For any language L in L over Σ, there exist an alphabet of k pairs of matching parentheses Xk, Dyck reduction Red over Xk, and a language L2 in L' over ΣXk such that L=Red(L2)Σ*. We also give an application of this result.

A noise reduction filter composed of a sandglass-type neural network (Sandglass-type Neural network Noise Reduction Filter: SNNRF) was proposed in the present paper. Sandglass-type neural network (SNN) has symmetrical layer construction, and consists of the same number of units in input and output layers and less number of units in a hidden layer. It is known that SNN has the property of processing signals which is equivalent to KL expansion after learning. We applied the recursive least square (RLS) method to learning of SNNRF, so that the SNNRF became able to process on-line noise reduction. This paper showed theoretically that SNNRF behaves most optimally when the number of units in the hidden layer is equal to the rank of covariance matrix of signal component included in input signal. Computer experiments confirmed that SNNRF acquired appropriate characteristics for noise reduction from input signals, and remarkably improved the SN ratio of the signals.

As the number of different video compression algorithms in use and also the specific bit rates at which they are operated increase, there is a growing need for converters from one algorithm or bit rate to another. In general, this can only be accomplished by decoding and re-encoding. It has previously been assumed that the additional delays introduced by such decoding and re-encoding are additive and thereby become unacceptable for some interactive applications. This paper shows that it is possible to construct a transcoder such that the aggregate end-to-end delay is substantially less than the sum of the delays from the two encode and decode pairs. Two techniques are described. The first is more general while the second is simpler but is restricted to the case of reducing the bit rate and keeping the same compression algorithm. Results from simulations of the latter method are included.

A new numerical technique, termed the method of matrix-order reduction (MMOR), is developed for handling electromagnetic problems in this paper, in which the matrix equation resulted from a method-of-moments analysis is converted either to an eigenvalue equation or to another matrix equation with the matrix order in both cases being much reduced, and also, the accuracy of solution obtained by solving either of above equations is improved by means of a newly proposed generalized Jacobian iteration. As a result, this technique enjoys the advantages of less computational expenses and a relatively good solution accuracy as well. To testify this new technique, a number of wire antennas are examined and the calculated results are compared with those obtained by using the method of moments.

We are working on an algorithm to optimize the logic circuits that can be realized on the super fine-grain parallel processing architecture. As a part of this work, we have developed an inverter reduction algorithm. This algorithm is based on modeling logic circuits as dynamical systems. We implement the algorithm in the PARTHENON system, which is the high level synthesis system developed in NTT's laboratories, and evaluate it using ISCAS85 benchmarks. We also compare the results with both the existing algorithm of PARTHENON and the algorithm of Jain and Bryant.

Let L be any class of languages, L' be a class of languages which is closed under λ-free homomorphisms, and Σ be any alphabet. In this paper, we show that if the following statement (1) holds, then the statement (2) holds. (1) For any language L in L over Σ, there exist an alphabet of k pairs of matching parentheses Xk, Dyck reduction Red over Xk, and a language L1 in L' over ΣXk such that L=Red(L1)Σ*. (2) For any language L in L over Σ, there exist an alphabet Γ including Σ, a homomorphism h : Γ*Σ*, a Dyck language D over Γ, and a language L2 in L' over Γ such that L=h(DL2). We also give an application of this result.

In-line transceiver chip emitting at 1.3 µm and receiving at 1.55 µm is described regarding the crosstalk occurring between the 1.3-µm laser and the 1.55-µm integrated photodiode. Contribution of optical and electrical crosstalk to the overall crosstalk is measured and discussed. Techniques to overcome the crosstalk are proposed and demonstrated by showing the feasibility of system compatible diplex sensitivities.

For reduction of computational complexity in the IA algorithm, the thinned-out IA algorithm in which only one step size is updated every iteration is proposed and is complementarily switched with the HA algorithm according to the convergence. The switching is determined by using the gradient of the error signal power. These are investigated through the computer simulations.

To make the model-based coding a practical method, new signal processing techniques other than fully-automatic image recognition should be studied. Also after having realized the model-based coding, another new signal processing technique to improve the performance of the model-based coding should be studied. Moreover non-coding functions related to the model-based coding can be embedded as additional features. The authors are studying the interactive model-based coding in order to achieve its practical realization, improve its performance and extend related non-coding functions. We have already proposed the basic concept of interactive model-based coding and presented an eyeglasses processing for a facial image with glasses to remove the frame for improving the model-based coding performance. In this paper, we focus on the 3-D motion detection algorithm in the interactive model-based coding. Previous works were mainly based on iterative methods to solve non-linear equations. A new motion detection algorithm is developed for interactive model-based coding. It is linear because the interactive operation generates more information and the environment of the applications limits the range of parameters. The depth parameter is first obtained by the fact that a line segment is invariant as to 3-D space transformation. Relation of distance between two points is utilized. The number of conditions is larger than that of the unknown variables, which allows to use least square method for obtaining stable solutions in the environment of the applications. Experiments are carried out using the proposed motion detection method and input noise problems are removed. Synthesized wireframe modified by eight parameters provides smooth and natural motion.