A new class of least-squares algorithms is presented for adaptive filtering. The idea is to use a fixed set of directions and perform line search with one direction at a time in a cyclic fashion. These algorithms are called Euclidean Direction Search (EDS) algorithms. The fast version of this class is called the Fast-EDS or FEDS algorithm. It is shown to have O(N) computational complexity and a convergence rate comparable to that of the RLS algorithm. Computer simulations are presented to illustrate the performance of the new algorithm.

Independent component analysis (ICA) is a new method of extracting independent components from multivariate data. It can be applied to various fields such as vision and auditory signal analysis, communication systems, and biomedical and brain engineering. There have been proposed a number of algorithms. The present article shows that most of them use estimating functions from the statistical point of view, and give a unified theory, based on information geometry, to elucidate the efficiency and stability of the algorithms. This gives new efficient adaptive algorithms useful for various problems.

This paper describes the outline of the active noise control system and the adaptive signal processing used in the practical systems. Focus is on the adaptive signal processing and algorithms which are widely used in many applications. Some variations in the algorithms for improving the control effect and for reducing the amount of calculation are also shown. Additionally, the limitations and some design guide are shown with the results of the numerical simulations.

In the field of computer graphics (CG), some adaptive methods have been proposed in order to make CG images more real in relatively low computational cost. As one of such adaptive methods, in this paper, an adaptive method will be proposed for detection of edges and approximation of surfaces in the use of the so-called automatic differentiation. In the proposed method a CG image with high quality can be generated in suitable computational cost. In this paper, three cases will be considered. The first is an adaptive distributed ray tracing which can adaptively generate anti-aliased CG images in suitable computational cost. The second is a high quality triangular meshing, which guarantees accuracy of the generated meshes according to shape of given surface in suitable computational cost. The last case is used in the so-called radiosity method.

As a center of mobile multimedia of the 21st century, it is very much looking forward to explosion of R&D and business of the next generation of mobile communication systems and the ITS (Intelligent Transport Systems) because ITS will enable information-oriented in the field of the road, traffic and vehicles, by using the most advanced technologies of mobile communications and devices, for the various purposes such as decrease of the traffic accident, the reduction of traffic jam, the increase in efficiency of the logistics and the harmony with the earth environment. This invited paper will first briefly introduce evolution of mobile communications and ITS in ministries, industries and academia in Japan. Then core communication technologies for ITS will be overviewed such as spread spectrum CDMA, adaptive antenna array, and software radio or software defined radio. Demands of SoC (System on a Chip) to carry out the core technologies will be addressed.

This paper proposes a maneuvering target tracking algorithm using multiple model filters. This filtering algorithm is discussed in terms of tracking performance, tracking success rate and tracking accuracies for short sampling interval as compared with other conventional methodology. Through several simulations, validity of this algorithm has been confirmed.

In this paper, we discuss digital watermarking techniques besed on modifying the spectral coefficient of an image, classified into quantization-based and correlation-based watermarking techniques. We first present a model of the watermark embedding and extracting processes and examine the robustness of the watermarking system against common image processing. Based on the result, we clarify the reason why detection errors occur in the watermark extracting process and give a method for evaluating the performance of the watermarking system. And then we study an improvement of the watermark extracting process using the deconvolution technique and present some concluding remarks in the last section.

Recent DSP applications have many significant issues such as higher system performance, lower power consumption, higher design flexibility, faster time-to-market, and so on. Neither a conventional ASIC nor a conventional DSP can necessarily satisfy all the requirements at once nowadays. Therefore, an alternate for DSP applications will be needed to complement the drawbacks of ASICs and DSPs. This paper introduces a new computing paradigm called configurable computing or reconfigurable computing, which has more potential in terms of performance and flexibility. Conventional silicon platforms will not satisfy the conflicting demands of standard products and customization. However, silicon platforms such as FPGAs for configurable or reconfigurable computing are standardized in manufacturing but customized in application. This paper also presents a brief survey of the existing silicon platforms that support configuration or reconfiguration in the application domain of digital signal processing such as image processing, communication processing, audio and speech processing. Finally, we show some promising reconfigurable architectures for the digital signal processing and discuss the future of reconfigurable computing.

Despite the enormous power of present-day computers, digital systems cannot respond to real-world events in real time. Biological systems, however, while being built with very slow chemical transistors, are very fast in such tasks like seeing, recognizing, and taking immediate actions. This paper discusses the issue of how we can build real-time intelligent systems directly on silicon. An intelligent VLSI system inspired by a psychological brain model is proposed. The system stores the past experience in the on-chip vast memory and recalls the maximum likelihood event to the current input based on the associative processor architecture. Although the system can be implemented in a CMOS digital technology, we are proposing here to implement the system using circuits operating in the analog/digital-merged decision making principle. Low-level processing is done in the analog domain in a fully parallel manner, which is immediately followed by a binary decision to yield answers in digital formats. Such a scheme would be very advantageous in achieving a high throughput computation under limited memory and computational resources usually encountered in mobile applications. Hardware-friendly algorithms have been developed for real-time image recognition using the associative processor architecture and some experimental results are demonstrated.

In the literature, the optimum discrete interpolation approximation is presented. However, this approximation is the optimum for the union of the set of band-limited signals and the set of the corresponding approximation errors. In this paper, under several assumptions, we present two optimum extended discrete interpolation approximations such that the set of the corresponding approximation errors is included in the set of signals if we ignore some negligible component of error. In this paper, we assume that the decimated sampling interval T satisfies T M, where M is the number of paths of the filter bank. The maximally distinct or under sampled filter banks treated in this paper have FIR analysis filters with or without a continuous pre-filter and FIR synthesis filters with a band-limited continuous D/A filter. The first discussion is useful for designing a kind of down-converter which transforms HDTV signal with wide band-width to SDTV signal with narrow band-width, for example. In this discussion, we assume that the SDTV signal is limited in |ω|π/T and the Fourier spectrum of the HDTV signal has wider band but is approximately included in the corresponding narrow band of the SDTV signal. In the well-known scalable coding of signals, if the spectrum of a signal with higher resolution is not included approximately in the spectrum of the corresponding signal with lower resolution, the quality of the quantized output signal with lower resolution will become quite low practically. As shown in [3], however, scalable coding has received much attention recently in the fields of HDTV/SDTV compatibility. Therefore, it will be natural to consider that the spectrum of HDTV signal with higher resolution is similar to and is included approximately in the corresponding spectrum of SDTV signal with lower resolution. The analysis filters are FIR filters with a continuous pre-filter approximately band-limited in |ω|π/T. To improve the quality of the SDTV signal, the whole spectrum component of the HDTV signal is used in the presented down-converter. Another discussion is a general theory of approximation for filter banks using the prescribed analysis filters. In this discussion, although some modification for the band-width is introduced in the process of analysis, the final band-width of the receiver is limited in |ω| π. The FIR analysis filters do not have pre-filter. The condition imposing on the set of signals is more general than the corresponding condition in the first optimum approximation theory. Finally, we present the optimum transmultiplexer TR. In general, under the condition that the receiver filters are prescribed, a transmultiplexer has approximation error between the original signal and the transferred signal. However, the presented TR minimizes approximately the supreme value of arbitrary positive measures of approximation error that can be defined, totally or separately, with respect to all the channels. Note that, in the presented discussion, we can prescribe the degree of FIR filters used in TR, strictly.

The constant-Q based wavelet transform is the most effective means of quantitatively characterizing high frequency transient signals. This study develops a novel non constant-Q based multi-resolution transform (NCQM) and provides a precision analysis descriptor for both low and high frequency transients. The properties of this novel NCQM kernel are thoroughly examined and then the striking conceptual resemblance, energy conservation characteristic, and power spectrum close forms are derived. The rapid algorithm of NCQM is also presented and its excellent performance in noisy environments is demonstrated.

In this paper, we study the fundamental combinatorial nonlinear resonances of a system consisting of two identical periodic forced circuits coupled by a linear resistor. The circuit equations are described by a system of coupled Duffing's equations. We discuss two cases of external periodic force, i.e., in-phase and anti-phase, and obtain the bifurcation diagram of each case. Periodic solutions are classified according to the symmetrical property of the circuit. Resonances in the coupled system are explained from the combinatorial standpoint. That is, we introduce the definition of combinatorial resonances and investigate the patterns of combinatorial solutions in this system.

In this paper, we propose an improved network-flow based multi-way circuit partitioning algorithm whose objective is to minimize the number of sub-circuits. It iteratively extracts a size-maximal feasible sub-circuit one at a time. In our approach, two devices are applied. One is in the use of an exact min-cut graph, and the other is in the idea of keeping the number of I/O pins of the residual circuit as small as possible after one-time extraction. We implemented our algorithm in C for experiments, and tested it with several industrial cases and MCNC benchmarks. Compared to the known approach, we observed more than 10% reduction in average of the sub-circuit number.

In Ref.[5], the author defines "approximate eigenvalues" and "approximate eigenvectors," which are, in short, Taylor series expansions of eigenvalues and eigenvectors of a polynomial matrix. In this paper, an efficient algorithm to compute the approximate eigenvalues and eigenvectors is presented. The algorithm performs the computations with an arbitrary degree of convergence.

This paper presents some new protocols for (M+1)st-price auction, a style of auction in which the highest M bidders win and pay a uniform price, determined by the (M+1)st price. A set of distributed servers collaborates to resolve the (M+1)st price without revealing any information in terms of bids including the winners' bids. A new trick to jointly and securely compute the highest value as a degree of distributed polynomials is introduced. The building block requires just one round for bidders to cast bids and one round for auctioneers to determine the winners.

Partition chains with balanced vectors are constructed in this paper. The partition chains can be constructed from weight distribution of Reed-Muller codes or randomization lemma. For the partition chain, its line coding parameters such as maximum runlength and running digital sum are obtained. The trellis and multilevel code structure can be used to design the error-correcting balanced codes. Especially, by adopting balanced trellis codes as constituent codes, balanced turbo codes can be designed. As results, the designed error-correcting balanced codes have good coding parameters.

We have proposed an intracell uplink of a spread-spectrum code-division multiple-access (SS-CDMA) flexible wireless network based on approximately synchronized (AS) CDMA. Since the AS-CDMA has no co-channel interference, complicated transmission power control (TPC) is not required. A modem of the AS-CDMA has been designed and implemented for the Japanese 2.4 GHz industrial, scientific and medical (ISM) band. Using the implemented modem, the degradation of E_b/N₀ from the theoretical limit is 1.0 dB at a bit error rate (BER) of 10^-3. Under 2-user environment, the degradation of carrier-to-noise ratio (CNR) is 0.5 dB at a BER of 10^-3 when the desired-to-undesired signal ratio (DUR) is -20.3 dB. We have evaluated BER performances in cases of varying carrier frequency offset and median DUR with computer simulation. Under 8-user environment, at the carrier frequency offset of 0.3 ppm, the BER with the DUR of -16 dB is found to be 10^-3. Using the AS-CDMA with a 4-step open-loop TPC technique, the design of intracell uplink is available.

A wavelet based algorithm for scalable video compression is described, with the main focus put on memory bandwidth reduction and efficient VLSI implementation. The proposed algorithm adopts a modified 2-D subband decomposition scheme in conjunction with a partial zerotree search for efficient Embedded Zerotree Wavelet coding. The experiment with the performance of the proposed algorithm in comparison with that of conventional DWT, MPEG-2, and JPEG demonstrates that the image quality of the proposed algorithm is consistently superior to that of JPEG, and our scheme can even outperform MPEG-2 in some cases, although it does not exploit the inter-frame redundancy. In spite of the performance inferiority to the conventional DWT, the proposed algorithm attains significant reduction of DWT memory requirements, enhancing a reasonable balance between implementation cost and image quality.

A fuzzy-like phenomenon is observed in a chaotic neural network operating as dynamic autoassociative memory. When an external stimulation with properties shared by two stored patterns is applied to the chaotic neural network, the output of the network transits between the two patterns. The ratio of the network visiting two stored patterns is dependent on the ratio of the Hamming distances between the external stimulation and the two stored patterns. This phenomenon is similar to the human decision-making process, which can be described by fuzzy set theory. Here, we analyze the fuzzy-like phenomenon from the viewpoint of the fuzzy set theory.

This paper presents an improved spectral subtraction method for speech enhancement. A new noise estimation method is derived in which the noise is assumed to be white. By using the property that a white noise spectrum is flat, high frequency components of a noisy speech spectrum are averaged and the standard deviation of the noise is estimated. This operation is performed in the analysis segment, thus the spectral subtraction method combined with the new noise estimation method does not need non-speech segments and as a result can adapt to non-stationary noise conditions. The effectiveness of the proposed spectral subtraction method is confirmed by experiments.