This paper addresses a simple, and yet effective approach to the design of block adaptive beamformers via parallel projection method (PPM), which is an extension of the classic projection onto convex set (POCS) method to inconsistent sets scenarios. The proposed approach begins with the construction of the convex constraint sets which the weight vector of the adaptive beamformer lies in. The convex sets are judiciously chosen to force the weights to possess some desirable properties or to meet some prescribed rules. Based on the minimum variance criterion and a fixed gain at the look direction, two constraint sets including the minimum variance constraint set and the gain constraint set are considered. For every input block of data, the weights of the proposed beamformer can then be determined by iteratively projecting the weight vector onto these convex sets until it converges. Furnished simulations show that the proposed beamformer provides superior performance compared with previous works in various scenarios but yet in general with lower computational overhead.

This paper considers the problem of recursive filtering for linear discrete-time systems with uncertain observation. A new approximate adaptive filter with a parallel structure is herein proposed. It is based on the optimal mean square combination of arbitrary number of correlated estimates which is also derived. The equation for error covariance characterizing the mean-square accuracy of the new filter is derived. In consequence of parallel structure of the filtering equations the parallel computers can be used for their design. It is shown that this filter is very effective for multisensor systems containing different types of sensors. A practical implementation issue to consider this filter is also addressed. Example demonstrates the accuracy and efficiency of the proposed filter.

This paper describes a new multi-channel method of noisy speech recognition, which estimates the log spectrum of speech at a close-talking microphone based on the multiple regression of the log spectra (MRLS) of noisy signals captured by distributed microphones. The advantages of the proposed method are as follows: 1) The method does not require a sensitive geometric layout, calibration of the sensors nor additional pre-processing for tracking the speech source; 2) System works in very small computation amounts; and 3) Regression weights can be statistically optimized over the given training data. Once the optimal regression weights are obtained by regression learning, they can be utilized to generate the estimated log spectrum in the recognition phase, where the speech of close-talking is no longer required. The performance of the proposed method is illustrated by speech recognition of real in-car dialogue data. In comparison to the nearest distant microphone and multi-microphone adaptive beamformer, the proposed approach obtains relative word error rate (WER) reductions of 9.8% and 3.6%, respectively.

This paper describes a polarimetric feature extraction method from urban areas using the POLSAR (Polarimetric Synthetic Aperture Radar) data. The scattering characteristic of urban areas is different from that of natural distributed areas. The main point of difference is polarimetric correlation coefficient, because urban areas do not satisfy property of azimuth symmetry, Shh = Shv = 0. The decomposition technique based on azimuth symmetry can not be applied to urban areas. We propose a new model fit suitable for urban areas. The proposed model fit consists of odd-bounce, even-bounce and cross scattering models. These scattering models can represent the polarimetric backscatter from urban areas, and satisfy Shh 0 and Shv 0. In addition, the combination with the proposed model fit and the three component scattering model suited for natural distributed areas is examined. It is possible to apply the combined technique to POLSAR data which includes both urban areas and natural distributed areas. The combined technique is used for feature extraction of actual X-band POLSAR data acquired by Pi-SAR. It is shown that the proposed model fit is useful to extract polarimetric features from urban areas.

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.

Broadband fixed wireless access (BFWA) systems with multi-hop mesh topologies have attracted considerable attention as a promising technology for next generation, high quality, high capacity, and high density access infrastructures. The primary advantages of mesh network topologies are an improvement of availability in connectivity between pairs of nodes by means of diversity routes. This paper discusses wireless node architecture that enables the integrated control of route diversity and traffic engineering together with the control of wireless links whose quality and performance could be affected by radio propagation conditions. Taking into account the functional requirements for multi-hop mesh BFWA networks, such as adaptive link configuration with multiple channels, distributed network management, and traffic engineering in mesh networks, the entity called network control unit (NCU) is designed and developed on a common UNIX based server computer. Implemented functions and their performance are demonstrated using the experimental environments with wired networks.

System-level fault diagnosis deals with the problem of identifying faulty nodes (processors) in a multiprocessor system. Each node is faulty or fault-free, and it can test other nodes in the system, and outputs the test results. The test result from a node is reliable if the node is fault-free, but the result is unreliable if it is faulty. In this paper, we prove that four variants of the hypercube: the crossed cube, the twisted cube, the Mobius cube, and the enhanced cube, are adaptively diagnosed using at most 4 parallel testing rounds, with at most n faulty nodes (for the enhanced cube, with at most n + 1 faulty nodes), where each processor participates in at most one test in each round. Furthermore, we propose another diagnosis algorithm for the n-dimensional enhanced cube with at most n + 1 faulty nodes, and show that it is adaptively diagnosed with at most 5 rounds in the worst case, but with at most 3 rounds if the number of existing faulty nodes is at most n -log(n + 1).

This paper describes an accurate unsupervised speaker adaptation method for lecture style spontaneous speech recognition using multiple LVCSR systems. In an unsupervised speaker adaptation framework, the improvement of recognition performance by adapting acoustic models remarkably depends on the accuracy of labels such as phonemes and syllables. Therefore, extraction of the adaptation data guided by confidence measure is effective for unsupervised adaptation. In this paper, we looked for the high confidence portions based on the agreement between two LVCSR systems, adapted acoustic models using the portions attached with high accurate labels, and then improved the recognition accuracy. We applied our method to the Corpus of Spontaneous Japanese (CSJ) and the method improved the recognition rate by about 2.1% in comparison with a traditional method.

This paper presents a multiple constrained subspace based multiuser detector for synchronous long-code downlink multirate DS-CDMA systems. The novel receiver adapts its fractionally-spaced equaliser tap-weights based upon two modes, namely training and decision-directed modes. Switching between two modes is achieved by changing the code constraint in the associated subspace algorithm. Moreover, detection of the desired user requires the knowledge of the desired user's spreading code only. Simulation results show that the proposed receiver is capable of multiple access interference (MAI) suppression and multipath mitigation. Besides, the results reveal the improvement in terms of convergence speed and mean square error (MSE) of the proposed receiver over the existing receiver in both static and dynamic environments.

Inverse synthetic aperture radar (ISAR) is useful for automatic target recognition (ATR) because it can reconstruct a high resolution image of an observed target. In ISAR imaging, 3-dimensional reflectivity distribution of a target is projected to the plane defined by range axis and cross range axis. In order to recognize the observed target by using pattern matching, reference images of candidate targets must be adequately generated. However, that is difficult because the cross range axis, which depends on the target's unknown rotational motion, can not be determined precisely. In this paper, we propose a new algorithm to generate reference ISAR images of ship targets. In this algorithm, tracking data, Doppler width and the slope of the centerline of an ISAR target image are used to specify the cross range axis. The effectiveness of the proposed algorithm was evaluated by using simulated targets.

In this paper, we propose an adaptive algorithm based on accumulated signal processing, which could be applicable to Post-FFT-type OFDM adaptive array antennas. Proposed scheme calculates the weight of each element at a particular instant t, by considering both post- and pre-received symbols. Because of the use of additional forthcoming information on channel behavior in the weight calculation scheme, one can expect an improved performance in fast fading conditions by using the proposed adaptive algorithm. This paper also discusses the application of the proposed adaptive algorithm to OFDM adaptive array. In OFDM application, a few subchannels are being used to transmit pilot symbols, and at the receiver, the proposed adaptive algorithm is applied to those pilot subchannels, and interpolates the weights for the data subchannels which are allocated between the pilot subchannels. Finally, the system performance improvement with the application of the proposed adaptive algorithm is verified by computer simulation.

In this paper, an efficient architecture for an adaptive Reed-Solomon decoder is presented, where the block length n and the message length k can be varied from their minimum allowable values up to their selected values. This eliminates the need of inserting zeros before decoding shortened RS codes. And the error-correcting capability t can be changed adaptively to channel state at every codeword block. The decoder allows efficient decoding in both burst mode and continuous mode, and it permits 3-step pipelined processing based on the modified Euclid's algorithm. Each step in decoding is designed to be clocked by a separate clock. Thus, each step can be efficiently pipelined with no help of multiplexing. Also, it makes it possible to employ no additional buffer even when the decoder input and output clocks are different. The adaptive RS decoder over GF(28) having the error-correcting capability of upto 10 has been designed in VHDL, and successfully synthesized in an FPGA chip. It can be used in a wide range of applications because of its versatility.

This paper proposes an OFDM based adaptive modulation scheme employing variable coding rate (VCR OFDM AMS), which selects optimum modulation and coding scheme (MCS) realized by combination of several modulation schemes and coding rates. The OFDM AMS with multilevel transmit power control (OFDM AMS/MTPC) can realize high data rate transmission in the dynamic parameter controlled-orthogonal frequency and time division multiple access (DPC-OF/TDMA). The employment of OFDM AMS/MTPC, however, makes transceiver design rather complex. To solve this problem, we propose to improve throughput performances of the OFDM AMS without employment of the MTPC. The simple OFDM AMS, however, does not fully utilize transmit power for throughput improvement because there is surplus transmit power which corresponds to power margin over required signal to interference plus noise power ratio (SINR). Thus, in order to improve transmit power efficiency for throughput increase, we reduce the required SINR gaps between adjacent MCSs by introducing many coding rates. Furthermore, this paper presents an effective bit loading algorithm when multiple coding rates as well as modulation schemes are used. Computer simulation confirms that the proposed VCR OFDM AMS gives sufficient throughput performances as an alternative to the OFDM AMS/MTPC.

A noise reduction technique to reduce background noise in noisy speech is proposed. We have proposed the noise reduction method which uses a noise reconstruction system. However, since a residual speech signal is included in the input signal of a noise reconstruction filter (NRF) used for reconstructing the background noise, the long time average value of error signal for estimating the background noise is needed not to estimate the speech signal. Therefore, the ability of tracking the non-stationary noise is decreased. In order to solve this problem, we propose the noise reconstruction system with adaptive line enhancer (ALE). Since ALE works to obtain the signal occupied by noise components, the input signal of the NRF includes only a few speech components. Therefore, we can give the high tracking ability to NRF.

Adaptive routing algorithms, which dynamically select the route of a packet, have been widely studied for interconnection networks in massively parallel computers. An output selection function (OSF), which decides the output channel when some legal channels are free, is essential for an adaptive routing. In this paper, we propose a simple and efficient OSF called minimal multiplexed and least-recently-used (MMLRU). The MMLRU selection function has the following simple strategies for distributing the traffic: 1) each router locally grasps the congestion information by the utilization ratio of its own physical channels; 2) it is divided into the two selection steps, the choice from available physical channels and the choice from available virtual channels. The MMLRU selection function can be used on any type of network topology and adaptive routing algorithm. Simulation results show that the MMLRU selection function improves throughput and latency especially when the number of dimension becomes larger or the number of nodes per dimension become larger.

The knowledge of channel state information (CSI) at the transmitter (TX), which in case of time division duplex (TDD) systems can be easily obtained due to radio channel reciprocity, can dramatically increase the spectral efficiency of a multiple-input multiple-output (MIMO) system. This paper presents a robust link adaptation method for TDD systems employing MIMO-OFDM channel eigenmode based signalling. We propose a rather simple logarithm-free, bit and power loading algorithm which requires low signalling overhead. Proposed method maintains constant frame error rate (FER) by controlling the instantaneous transmitted power in such a way that the average SNR at the equalizer output is kept constant. The scheme takes into account channel estimation errors at TX side by partial compensation of the SNR estimation errors. By using a simple scalar channel encoder, for an unbalanced MIMO system with larger number of transmit than receive antennas, the achieved spectral efficiency at low and medium SNR is significantly higher than the outage MIMO capacity with unknown CSI at the TX. The simulation results show that for a constant FER, the throughput degradation compared to the universally accepted Hughes-Hartogs algorithm is negligible.

In this letter, a method to construct good binary and quaternary error correcting codes, called complex Hadamard codes, based on a complex Hadamard matrix is presented. The related properties of the codes are analyzed. In addition, through the operation in Z4 domain, a new simplex soft-decision decoding algorithm for the complex Hadamard codes is also proposed.

The design, manufacture, and test results are presented for a 90polarization-rotating Van Atta array reflector with suppressed scattered field for the 1.27-GHz band. The reflector consists of 48 element antennas, half for horizontal polarization and half for vertical polarization. It receives a horizontally or vertically polarized wave and retransmits a vertically or horizontally polarized wave, respectively. The measured cross-polarized radar cross section of the reflector was 15.8 dBm2 on average, which agreed well with a theoretical prediction. Although the suppression of the scattered field was limited to about -20 dB relative to the retransmitted field, we could suppress more the scattered field by accurate positioning and careful characteristics adjustment of element antennas. Theoretical calculations showed that total phase errors of the element antennas including positioning errors and impedance characteristics errors have to be within 7.5to suppress the scattered field by less than -30 dB.

An adaptive interpolated FIR (IFIR) echo canceller was recently proposed for xDSL applications. This canceller consists of an FIR filter, an IFIR filter, and a tap-weight overlapping and nulling scheme. The FIR filter is used to cancel the short and rapidly changing head echo while the IFIR filter is used to cancel the long and slowly decaying tail echo. This echo canceller, which inherits the stable characteristics of the conventional FIR filter, requires low computational complexity. It is well known that the interpolation filter for an IFIR filter has great influence on the interpolated result. In this paper, a least-squares method is proposed to obtain optimal interpolation filters such that the performance of the IFIR echo canceller can be further improved. Simulations with a wide variety of loop topologies show that the optimal IFIR echo canceller can effectively cancel the echo up to 73.0 dB (for an SHDSL system). About 57% complexity reduction can be achieved compared to a conventional FIR filter.

The power system and the battery management of mobile phones used by NTT DoCoMo subscribers will be described. The energy requirements of the phones' AC-adaptors (chargers), their power-management systems, and trends in energy consumption will be focused on. The results of the new Li-ion batteries' safety tests, quick tests assessing battery capacity deterioration, and battery lifetime predictions will be also discussed.