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.

A flash analog-to-digital converter (ADC) that uses resonant-tunneling complex gates is proposed. The ternary quantizers, consisting of monostable-to-multistable transition logic (MML) circuits, convert the analog input signal into the ternary thermometer code. This code is then converted into the binary Gray-code output by a multiple-valued multiple-input monostable-bistable transition logic element (M2-MOBILE). By assuming InP-based resonant-tunneling diode (RTD) and heterojunction field-effect transistor technology, we have carried out SPICE simulation that demonstrates a 4-bit, 10-GS/s ADC operation. The input bandwidth, defined as a frequency at which the effective number of bit decreases by 0.5 LSB, was also estimated to be 500 MHz. Compact circuit configuration, which is due to the combination of MML and M2-MOBILE, reduces the device count and power dissipation by a factor of two compared with previous RTD-based ADCs.

We present the design of dual rail Data Driven Self Timed (DDST) DEMUX and MUX circuits for 50 GHz operation. The chosen current density is 6.5 kA/cm2 and simulations show good margins for speeds exceeding 50 GHz. Our previously reported dual-rail on-chip test system is also scaled up for 50 GHz operation.

This letter proposes a 3-D stereo endoscopic image processing system. Whereas a conventional 3-D stereo endoscopic system has simple monitoring functions, the proposed system gives doctors exact depth feelings by providing them depth value information, visualization, and stereo PACS viewer to aid an education, accurate diagnosis, a surgical operation, and to further apply in a robotic surgery.

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.

Achieving optimal performance with minimal complexity are conflicting problems encountered in constructing receivers. In this paper, to solve the problem, we propose sector beamed space hopping which utilizes a Viterbi equalizing receiver. Reduction of the number of RF circuit sets, system complexity and decreasing the computational burden of the Viterbi equalizer through the use of sector beamed space hopping is presented. This is achieved using a sector beamed antenna which limits the number of paths in the multipath channel environment. This paper describes each key component which comprises the system and discusses the application of FH-SS communication. The channel is assumed to be an industrial indoor propagation channel, such as those found in a factory, where high reliability is required and many complex multipaths exist. We confirm through simulation that Viterbi equalization using less computational complexity can be obtained. It is found that there exists a trade off between system complexity and performance. Through the discussion of power consumption, cost and BER performance, we show that the proposed system achieves acceptable performance while having a low system complexity.

In this paper, characteristics of a digital system dedicated to the fast execution of the FDTD algorithm, widely used for electromagnetic simulation, are presented. Such system is conceived as a module communicating with a host personal computer via a PCI bus, and is based on a VLSI ASIC, which implements the "field-update" engine. The system structure is defined by means of a hardware description language, allowing to keep high-level system specification independent of the actual fabrication technology. A virtual implementation of the system has been carried out, by mapping such description in a standard-cell style on a commercial 0.35 µm technology. Simulations show that significant speed-up can be achieved, with respect to state-of-the-art software implementations of the same algorithm.

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.

Scalabilities of bit rate and coding format in coded multimedia contents have become very important for the efficient use of network bandwidth and storage capacity with the recent availability of a wide variety of bandwidth and storage media. However, the conventional approach uses decompression and recompression processes to realize the above scalabilities, which require very expensive computations. In addition, a very large cache space is required for storing the decoded audio-video data. This paper describes three fast scalability methods for MPEG audio and video data, MPEG audio/video bit rate conversion and MPEG format conversion, in order to address these problems. As for the first scalability, MPEG audio coding bit rate conversions, we describe subband domain conversion using bandwidth limitation, requantization and a requantization reflecting phychoacoustic model. Four types of MPEG video bit rate conversion are described that use bandwidth limitation, out-loop requantization, in-loop requantization, and hybrid requantization. As for the format conversion, the fast baseband domain format conversion is performed using coding information such as motion vectors and coding types extracted from input coded video. The experimental results of several comparisons with the above scalabilities and conventional transcoding methods are also shown.

This contribution discusses which information can be derived from estimated directions of arrival (DOAs) and directions of departure (DODs) from a multiple-input multiple-output (MIMO) radio system, and establishes two new parameters describing the multipath spread at both link ends. We find that the multipath component separation, MCS, combines delay, (double-) angular and Doppler dispersion, as appropriate. MCS provides a system-independent radio characterization of propagation environments and aids in selecting optimum positions for smart-antenna deployment. Evaluation of double-directional measurements (antenna arrays at both link ends) in indoor environments show the usefulness and the limits of the multipath component separation concept.

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.

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.

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 this letter, an algorithm that estimates one of the most important channel parameters, maximum Doppler frequency, fD, is proposed. The algorithm uses phase variations of received pilot signals, which is strongly related with fD in a fading environment. In addition, a phase variation measurement method for binary phase shift keying (BPSK) modulated signals is also proposed and it makes possible to estimate fD from BPSK modulated information signals as well as unmodulated pilot signals. The results show that the proposed algorithm is very simple and shows good performance over wide Doppler frequency range.

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.

This paper introduces a probabilistic modeling of alarm observation delay, and shows a novel method of model-based diagnosis for time series observation. First, a fault model is defined by associating an event tree rooted by each fault hypothesis with probabilistic variables representing temporal delay. The most probable hypothesis is obtained by selecting one whose Akaike information criterion (AIC) is minimal. It is proved by simulation that the AIC-based hypothesis selection achieves a high precision in diagnosis.

Almost all land animals coordinate their behavior with circadian rhythms, matching their functions to the daily cycles of lightness and darkness that result from the rotation of the earth corresponding to 24 hours. Through external stimuli, such as dairy life activities or other sources from our environment may influence the internal rhythmicity of sleep and waking properties. However, the rhythms are regulated to keep their activity constant by homeostasis while fluctuating by incessant influences of external forces. A modeling study has been developed to identify homeostatic dynamics properties underlying a circadian rhythm activity of Sleep and Wake data measured from normal subjects, using an MA (Moving Average) model associated with Backpropagation (BP) algorithm. As results, we found that the neural network can capture the regularity and irregularity components included in the data. The order of MA neural network model depends on subjects behavior, the first two orders are usually dominant in the case of no strong external forces. The adaptive dynamic changes are evaluated by the change of weight vectors, a kind of internal representation of the trained network. The dynamic is kept in a steady state for more than 20 days at most. Identified properties reflect the subject's behavior, and hence may be useful for medical diagnoses of disorders related to circadian rhythms.

The size dependent properties of the intrinsic Josephson junctions in Bi2Sr2CaCu2Oy single crystal mesas in the external magnetic field are studied. The mesas of (1-140) µm long with 7-29 junctions were fabricated and their current-voltage characteristics were measured in external magnetic field applied parallel to the CuO2 layers up to 0.16 T. In zero magnetic field, multiple resistive branches with large hysteresis were observed in the current-voltage characteristics for the fabricated mesas. Almost identical critical currents were also observed for all the junctions in each mesa. With applied magnetic field, Ic of the longer mesas showed a complex magnetic field dependence as compared to that of the short mesas (of about 1 µm in length). It was observed that the lower critical magnetic field of the junctions decreased and approached a constant value with increasing number of junctions and also with increasing length of the junctions. Similar magnetic behavior was obtained by numerical simulations based on coupled sine-Gordon equations for such stacked junctions.

We studied the possibility of making an objective diagnosis of dementia based on radiological findings by evaluating cerebral and hippocampal atrophy and the corpus callosum shape on MRI images in patients with Alzheimer-type dementia, compared with healthy elderly individuals. There was a statistically significant difference in the hippocampus area index, the ventricle area index, and the area ratio for the second, forth, and fifth parts of corpus callosum. Discriminant analysis using these three parameters demonstrated the sensitivity of 88.5% and the specificity of 85.7%, suggesting a highly positive diagnostic rate. These results indicate that quantitative MRI measurements could be used for differentiating Alzheimer-type dementia from similar diseases.

An optical detection system using a DFB laser with a very small aperture is theoretically proposed. The threshold gain level in DFB laser is sensitively varied with combined reflections by the facet and the corrugation as well as with the optical injection reflected at the surface of the optical disk. Variation of the threshold gain level is counted as the voltage change on electrodes of the laser. It is found that sensitivity of the optical detection with a well-designed DFB laser becomes six times larger than that with conventional Fabry-Perot ones. Field distribution around the small aperture is analyzed taking into account both the near-field and the radiation field. Numerical data on the voltage change are given as examples of the detection system.