This paper attempts to use the polarimetric correlation coefficient for extraction of the polarimetric features of the urban areas and the natural distributed areas from Polarimetric Synthetic Aperture Radar (POLSAR) data. There is a possibility that the polarimetric correlation coefficient can reveal various scattering mechanisms of terrains based on the reflection symmetry property. In order to verify the capability of polarimetric correlation coefficient, we examined the behavior of this coefficient of the urban areas and the natural distributed areas with respect to the several polarimetric scattering models in the linear and circular polarization bases, and the difference of the polarimetric scattering characteristics between these two areas was derived. It was confirmed that the polarimetric correlation coefficient is useful to extract the polarimetric features from the actual L-band and X-band POLSAR data.

This paper describes a new interface for a barge-in free spoken dialogue system combining an adaptive sound field control and a microphone array. In order to actualize robustness against the change of transfer functions due to the various interferences, the barge-in free spoken dialogue system which uses sound field control and a microphone array has been proposed by one of the authors. However, this method cannot follow the change of transfer functions because the method consists of fixed filters. To solve the problem, we introduce a new adaptive sound field control that follows the change of transfer functions.

We have proposed a novel spatial filtering technique named "VIrtual Subcarrier Assignment (VISA)" for orthogonal frequency division multiplexing (OFDM) signals, which enables the transceiver equipped with an adaptive array antenna (AAA) to selectively receive or reject OFDM signals through coloring them with different virtual subcarrier positions in their frequency spectra. In this paper, we develop the VISA to use multiple virtual subcarrier assignment, which assigns a different combination of multiple virtual subcarrier positions in the frequency spectrum to each OFDM signal. Furthermore, we present two kinds of recursive least square (RLS)-based array weight control methods to support the VISA with multiple subcarrier puncturing in an IEEE802.11a-based system and evaluate the link-level performance in typical indoor wireless environments by computer simulations.

We present a simple bit allocation scheme based on adaptive coding for MIMO-OFDM (Multiple Input Multiple Output - Orthogonal Frequency Division Multiplexing) systems with V-BLAST (Vertical-Bell laboratories LAyered Space-Time) detector. The proposed scheme controls the code rate of the channel coding and assigns the same modulation and coding to the set of selected sub-channels, which greatly reduces the feedback burden while achieving good performance. Simulation results show that the proposed scheme with minimal feedback provides significant performance improvement over other systems.

In this paper, a modified adaptive fuzzy sliding mode controller for a certain class of uncertain nonlinear systems is presented. We incorporate the fuzzy sliding mode control technique with a modified adaptive fuzzy control technique to design a modified adaptive fuzzy sliding mode controller so that the proposed controller is robust against the unmodeled dynamics and the approximation errors. Firstly, we establish a fuzzy model to describe the dynamic characteristics of the given uncertain nonlinear system. Then, based on the fuzzy model, a fuzzy sliding mode controller is designed. By considering both the information of tracking error and modeling error, the modified adaptive laws for tuning the adjustable parameters of the fuzzy model are derived based on the Lyapunov synthesis approach. Since the modified adaptive laws contain both the tracking error and the modeling error, it implies that the fuzzy model parameters would continuously converge until both the tracking error and modeling error converges to zero. An inverted pendulum control system is simulated to demonstrate the control performance by using the proposed method.

To understand radio propagation structures and consider signal recovering techniques in mobile communications, it is most effective to estimate the signal parameters (e.g., DOA) of individual incoming waves. Also, in radar systems, it is required to discriminate the desired signal from interference. As one of the high-resolution DOA estimators, MUSIC and ESPRIT have attracted considerable attention in recent years. They need the eigenvectors of the correlation matrix and therefore we have to execute the EVD (eigenvalue decomposition) of correlation matrix. However, the EVD generally brings us a heavy computational load and as a result it is difficult to realize the real-time DOA estimator, which will be useful as a multibeam-forming algorithm for adaptive antennas. This paper focuses on MUSIC and ESPRIT using subspace tracking methods, such as BiSVD, PAST, and PASTd, to carry out iterative DOA estimation. Then, they are compared through computer simulation. Adaptive beamforming based on DCMP and MLM is also mentioned and an example is shown.

This paper proposes a new angular measurement system to a moving target in the presence of clutter. We apply MUSIC (MUltiple SIgnal Classification) to the outputs of a Doppler filter bank consisting of quadrature mirror filter (QMF). The comparison between QMF and the short time Fourier transform (STFT) as a preprocessor of MUSIC is also discussed. DOA estimation performance by QMF-MUSIC is nearly equal to that of STFT-MUSIC. On the other hand, QMF-MUSIC overcomes STFT-MUSIC in the aspect of computational cost. In a specific example in this paper, the proposal QMF bank by Daubechies (4th order) wavelet requires 80% fewer the number of multiplications and 25% fewer the number of additions than the FFT-based STFT filter bank.

The playout delay for voice over IP applications is adjusted on every talkspurt. The parameter β that controls the delay/packet loss ratio is usually fixed, based on high jitter conditions. In this letter, a β-adaptive playout algorithm is presented, where the β is adjusted. The buffering delays and lateness rates are compared against the existing algorithm with the fixed β. We show that the β-adaptive system improves the lateness loss performance, especially for low jitter conditions, while maintaining almost identical buffering delay/lateness loss performance when jitter is high.

This study proposes a novel adaptive fuzzy control methodology to remove disadvantages of traditional fuzzy approximation based control. Meanwhile, the highly uncertain robot manipulator is taken as an application with either guaranteed robust tracking performances or asymptotic stability in a global sense. First, the design concept, namely, feedforward fuzzy approximation based control, is introduced for a simple uncertain system. Here the desired commands are utilized as the inputs of the Takagi-Sugeno (T-S) fuzzy system to closely compensate the unknown feedforward term required during steady state. Different to traditional works, the assumption on bounded fuzzy approximation error is not needed, while this scheme allows easier implementation architecture. Next, the concept is extended to controlling manipulators and achieves global robust tracking performances. Note that a linear matrix inequality (LMI) technique is applied and provides an easier gain design. Finally, numerical simulations are carried out on a two-link robot to illustrate the expected performances.

This paper proposes a direct blind equalization algorithm based on the multiple-shift correlation (MSC) property of the received data. Employing adaptive beamforming technique, we develope a partially adaptive channel equalizer (PACE) which allows the number of the adaptive weights to be less than the number of all the channel parameters. The PACE is with fast convergence speed and low implementation complexity. This paper also analyzes the effect of mismatch of channel order estimation due to small head and tail of the channel impulse response. From the analysis, we show the performance degradation is a function of the optimal output signal-to-interference plus noise ratio (SINR), the optimal output power and the control vector. We also propose a simple iterative method to reudce the performance degradation. Analysis of this proposed iterative method is also performed. Some simulation examples are demonstrated to show the effectiveness of the proposed blind channel equalizer and the performance analysis.

In this paper, an adaptive microphone array system with a two-stage adaptation mode controller (AMC) is proposed for high-quality speech acquisition in real environments. The proposed system includes an adaptive array algorithm, a time-delay estimator and a newly proposed AMC. To ensure proper adaptation of the adaptive array algorithm, the proposed AMC uses not only temporal information, but also spatial information. The proposed AMC is constructed with two processing stages: an initialization stage and a running stage. In the initialization stage, a sound source localization technique is adopted, and a signal correlation characteristic is used in the running stage. For the adaptive array algorithm, a generalized sidelobe canceller with an adaptive blocking matrix is used. The proposed algorithm is implemented as a real-time man-machine interface module of a home-agent robot. Simulation results show 13 dB SINR improvement with the speaker sitting 2 m distance from the home-agent robot. The speech recognition rate is also enhanced by 32% when compared to the single channel acquisition system.

In this paper, a new algorithm for MTMR adaptive array antenna (AAA) system combined with analog-type transmit power control (TPC) is proposed for DS-CDMA systems in order to employ high level modulation schemes like 64 QAM in wireless multimedia services. A conventional AAA system considering the strongest path as a target path cannot work effectively when angular dispersion between the strongest path and other delayed paths is large, that is, beam selectivity is so small due to severe frequency selective multipath fading. So, in order to solve such a beam selectivity problem, a beam directivity control scheme using a path manipulation technique is introduced for the BS and MS AAA combining in this paper, along with analog-type TPC. It utilizes virtual delay profiles which are modified from the measured complex delay profile and selects a desired path giving the maximum DUR with an optimized weight vector for BS and MS beamforming. We will show through computer simulation that the proposed scheme is very effective in enhancing the data throughput at the downlink of wideband DS-CDMA systems as compared with the conventional system.

This paper proposes a Voice Activity Detection (VAD) algorithm using Radial Basis Function (RBF) network. The k-means clustering and Least Mean Square (LMS) algorithm are used to update the RBF network to the underlying speech condition. The inputs for RBF are the three parameters a Code Excited Linear Prediction (CELP) coder, which works stably under various background noise levels. Adaptive hangover threshold applies in RBF-VAD for reducing error, because threshold value has trade off effect in VAD decision. The experimental results show that the proposed VAD algorithm achieves better performance than G.729 Annex B at any noise level.

In this letter, pilot-assisted adaptive prediction iterative channel estimation in frequency-domain is presented for the antenna diversity reception of orthogonal frequency division multiplexing (OFDM) signals. A frequency-domain adaptive prediction filtering is applied to iterative channel estimation for improving the tracking capability against frequency-domain variations in a severe frequency-selective fading channel. Also, in order to track the changing fading environment, the tap weights of frequency-domain prediction filter are updated using the simple NLMS algorithm. Updating of tap weights is incorporated into the iterative channel estimation loop to achieve faster convergence rate. The average bit error rate (BER) performance in a frequency-selective Rayleigh fading channel is evaluated by computer simulation. It is confirmed that the frequency-domain adaptive prediction iterative channel estimation provides better BER performance than the conventional iterative channel estimation schemes.

Bayesian combining of confidence measures is proposed for speech recognition. Bayesian combining is achieved by the estimation of joint pdf of confidence feature vector in correct and incorrect hypothesis classes. In addition, the adaptation of a confidence score using the pdf is presented. The proposed methods reduced the classification error rate by 18% from the conventional single feature based confidence scoring method in isolated word Out-of-Vocabulary rejection test.

In this paper, a Dynamic Voltage and Frequency Management (DVFM) scheme introduced in a microprocessor for handheld devices with wideband embedded DRAM is reported. Our DVFM scheme reduces the power consumption effectively by cooperation of the autonomous clock frequency control and the adaptive supply voltage control. The clock frequency is controlled using hardware activity information to determine the minimum value required by the current processor load. This clock frequency control is realized without special power management software. The supply voltage is controlled according to the delay information provided from a delay synthesizer circuit, which consists of three programmable delay components, gate delay, RC delay and a rise/fall delay. The delay synthesizer circuit emulates the critical-path delay within 4% voltage accuracy over the full range of process deviation and voltage. This accurate tracking ability realizes the supply voltage scaling according to the fluctuation of the LSI's characteristic caused by the temperature and process deviation. The DVFM contributes not only the dynamic power reduction, but also the leakage power reduction. This microprocessor, fabricated in 0.18 µm CMOS embedded DRAM technology achieves 82% power reduction in a Personal Information Management scheduler (PIM) application and 40% power reduction in a MPEG4 movie playback application. As process technology shrinks, the DVFM scheme with leakage power compensation effect will become more important realizing in high-performance and low-power mobile consumer applications.

Global computing system (GCS) harnesses the idle CPU resources of clients connected to Internet for solving large problems that require high volume of computing power. Since GCS scale to millions of clients, many projects usually adopt coarse-grained scheduling in order to reduce server-side contention at the expense of sacrificing the degree of parallelism and wasting CPU resources. In this paper, we propose a new type of client, i.e., a scheduling proxy that enables adaptive-grained scheduling between the server and clients. While the server allocates coarse-grained work units to scheduling proxies alone, clients download fine-grained work units from a relatively nearby scheduling proxy not from the distant server. By computation of small work units at client side, the turnaround time of work unit can be reduced and the waste of CPU time by timeout can be minimized without increasing the performance cost of contention at the server. In addition, in order not to lose results in the failure of scheduling proxies, we suggest a technique of result caching in clients.

This paper addresses the estimation of time delay between two spatially separated noisy signals by system identification modeling with the input and output corrupted by additive white Gaussian noise. The proposed method is based on a modified adaptive Butler-Cantoni equalizer that decouples noise variance estimation from channel estimation. The bias in time delay estimates that is induced by input noise is reduced by an IIR whitening filter whose coefficients are found by the Burg algorithm. For step time-variant delays, a dual mode operation scheme is adopted in which we define a normal operating (tracking) mode and an interrupt operating (optimization) mode. In the tracking mode, only a few coefficients of the impulse response vector are monitored through L1-normed finite forward differences tracking, while in the optimization mode, the time delay optimized. Simulation results confirm the superiority of the proposed approach at low signal-to-noise ratios.

Appropriate language modeling is one of the major issues for automatic transcription of spontaneous speech. We propose an adaptation method for statistical language models based on both topic and speaker characteristics. This approach is applied for automatic transcription of meetings and panel discussions, in which multiple participants speak on a given topic in their own speaking style. A baseline language model is a mixture of two models, which are trained with different corpora covering various topics and speakers, respectively. Then, probabilistic latent semantic analysis (PLSA) is performed on the same respective corpora and the initial ASR result to provide two sets of unigram probabilities conditioned on input speech, with regard to topics and speaker characteristics, respectively. Finally, the baseline model is adapted by scaling N-gram probabilities with these unigram probabilities. For speaker adaptation purpose, we make use of a portion of the Corpus of Spontaneous Japanese (CSJ) in which a large number of speakers gave talks for given topics. Experimental evaluation with real discussions showed that both topic and speaker adaptation reduced test-set perplexity, and in total, an average reduction rate of 8.5% was obtained. Furthermore, improvement on word accuracy was also achieved by the proposed adaptation method.

This paper overviews recent progress in the development of corpus-based spontaneous speech recognition technology. Although speech is in almost any situation spontaneous, recognition of spontaneous speech is an area which has only recently emerged in the field of automatic speech recognition. Broadening the application of speech recognition depends crucially on raising recognition performance for spontaneous speech. For this purpose, it is necessary to build large spontaneous speech corpora for constructing acoustic and language models. This paper focuses on various achievements of a Japanese 5-year national project "Spontaneous Speech: Corpus and Processing Technology" that has recently been completed. Because of various spontaneous-speech specific phenomena, such as filled pauses, repairs, hesitations, repetitions and disfluencies, recognition of spontaneous speech requires various new techniques. These new techniques include flexible acoustic modeling, sentence boundary detection, pronunciation modeling, acoustic as well as language model adaptation, and automatic summarization. Particularly automatic summarization including indexing, a process which extracts important and reliable parts of the automatic transcription, is expected to play an important role in building various speech archives, speech-based information retrieval systems, and human-computer dialogue systems.