This paper proposes an adaptive list-output Viterbi equalizer (LVE) with fast compare-select operation, in order to achieve a good trade-off between bit error rate (BER) performance and processing speed. An LVE, which keeps several survivors for each state, has good BER performance in the presence of wide-spread intersymbol interference. However, the LVE suffers from large processing delay due to its sorting-based compare-select operation. The proposed adaptive LVE greatly reduces its processing delay, because it simplifies compare-select operation. In addition, computer simulation shows that the proposed LVE causes only slight BER performance degradation due to its simplification of compare-select operation. Thus, the proposed LVE achieves better BER performance than decision-feedback sequence estimation (DFSE) without an increase in processing delay.

This paper proposes a simple adaptive channel estimation scheme for orthogonal frequency division multiplexing (OFDM) in order to realize high-rate wireless local area networks (LANs). The proposed estimator consists of simple frequency-domain FIR filters, which are adaptively selected according to the difference vector between adjacent subcarriers and channel amplitude of the subcarrier. No precomputation or matrix signal processing is required in the derivation of these characteristics. Computer simulations show that the packet error rate performance of the proposed scheme is superior to that of the least-squares scheme by 1.1 dB in terms of required Eb/N0 at PER=0.1 in AWGN channels. They also show, for the same criterion, a 0.7 dB improvement in a frequency selective fading channel with delay spread values of 100 ns.

Adaptability evaluation of software systems is one of the key concerns in both software engineering and requirements engineering. In this paper, we present a formal and systematic approach to evaluate adaptability of software systems to requirements in enterprise business applications. Our approach consists of three major parts, that is, the common modeling method for both business realms and software realms, functional adaptability evaluation between the models with Σ algebra and behavioral adaptability evaluation with process algebra. By our approach, one can rigorously and uniquely determine whether a software system is adaptable to the requirements, either totally or partially. A sample application from an order processing is illustrated to show how this approach is effective in solving the adaptability evolution problem.

The constant modulus algorithm (CMA) of the adaptive array has been developed for suppressing the co-channel interference and the intersymbol interference in mobile communications. In this paper a novel CMA for the hybrid of the adaptive array and equalizer (HAE) is proposed to combat the problems of insufficient degrees of freedom and mainbeam multipath interferers. The HAE with CMA utilizes the constant modulus property for the output signal of the HAE to adjust the weight vectors of the array and equalizer simultaneously. The co-channel interferers can be canceled by the array and the multipath interferers can be removed by the array or the equalizer following the array in the HAE. Therefore, the array in the HAE with CMA may need less number of elements than that required by the CMA array which cancels both the co-channel interferers and multipath interferers. Besides, the presence of the mainbeam multipath interferers, which may seriously degrade the performance of the CMA array, has much less effect on the HAE with CMA since it can be suppressed by the equalizer instead of the array. Simulation results are presented to demonstrate the merits of the CMA for the HAE.

We have developed an active Q adaptor (AQA) to achieve integration of multiple management protocols and dynamic modification of managed object (MO) definitions. To achieve dynamic modification, we introduce a new MO framework, called dynamic-MO, which has the ability of modifying its own definition. A dynamic-MO is composed of meta-data and some behavior programs. Meta-data lists attributes of a dynamic-MO in a text format and a behavior program describes actions of a dynamic-MO in scripting language such as Java, Tcl, etc. In our AQA architecture, modules which manage individual components of a dynamic-MO communicate among themselves via an object request broker (ORB) in order to achieve system scalability with high performance. To realize the functionality of a dynamic-MO, we propose interfaces among these modules that are independent of dynamic-MO definitions and an update mechanism of behavior programs. We define the interfaces based on the common management information protocol (CMIP) operations to avoid re-defining the interfaces when dynamic-MO definitions are modified. Furthermore, to execute modified behavior programs without any negative influence on the workings of the other behavior programs, we employ a Java class-loader which has its own specific naming-space on a Java virtual machine (Java VM). With all of these features, our AQA is extremely promising for developing programmable network management systems for end-to-end management of heterogeneous telecommunication networks.

A procedure for radar target discrimination is presented in this paper. The scheme includes an enhancement of late-time noisy scattering data based on a proposed signal processing algorithm and a decision procedure using previously known resonance annihilation filters. The signal processing stage is specifically adapted to scattering signals and makes use of the results of the singularity expansion method. It is based on a signal reconstruction using the SVD of a data matrix with a suitable choice of the number of singular vectors employed. To justify the inclusion of this stage, this procedure is shown to maintain the signal characteristics necessary to identify the scattered response. Simulation results clearly reveal a significant improvement due to the inclusion of the proposed stage. This improvement becomes especially important when the noise level is high or the targets to be discriminated (five regular polygonal loops) have a similar geometry.

In this paper, fast algorithms for the CMA (constant modulus algorithm), which is one of the widely used algorithms for blind equalizationi are presented. We propose the FBCMA (frequency domain block CMA) which takes advantage of fast linear convolution in the DFT domain by using the overlap save method. For the FBCMA, a nonlinear error function in the frequency domain is derived using Parseval's relation. Also, an adaptive algorithm in the DFT domain is introduced to adjust the frequency domain filter coefficients. For a block size and filter length of N, the multiplications required for the conventional CMA and proposed FBCMA are on the order of O(N2) and O(N log N), respectively.

In this paper, the use of optimal Karhunen-Loeve (KL) transform for quantization of speech line spectrum frequency (LSF) coefficients is studied. Both scalar quantizer (SQ) and vector quantizer (VQ) schemes are developed to encode efficiently the transform parameters after operating one or two-dimensional KL transform. Furthermore, the SQ schemes are also combined with entropy coding by using Huffman variable length coding (VLC). The basic idea in developing these schemes is utilizing the strong correlation of LSF parameters to reduce the bit rate for a given level of fidelity. Since the use of global statistics for generating the coding scheme may not be appropriate, we propose several adaptive KL transform systems (AKL) to encode the LSF parameters. The performance of all systems for different bit rates is investigated and adequate comparisons are made. It is shown that the proposed KL transform coding systems introduce as good as or better performance for both SQ and VQ in the examined bit rates compared to other methods in the field of LSF coding.

Adaptive channel estimation filters are presented for coherent DS-CDMA reverse link using time-multiplexed pilot and parallel pilot structures. Fast transmit power control (TPC) is adopted in the reverse link. Fading statistical properties are not preserved when fast TPC is used. When fading is slow, the channel is similar to non-fading channel, but its starts to vary as fading become faster since fast TPC cannot track fading perfectly. A pragmatic approach is used in this paper to derive adaptive channel estimation filter. The filter coefficients are updated based on the measured autocorrelation function of the instantaneous channel estimate. The bit error rate (BER) performance under frequency selective Rayleigh fading is evaluated by computer simulation to show that the adaptive channel estimation filter provides superior performance to the previously proposed non-adaptive WMSA filter.

A RAKE receiver accomplishing joint blind multipath diversity combining and PN code timing recovery is proposed for direct-sequence spread-spectrum signaling over a frequency-selective fading channel. In this technique, an improved known modulus adaptive algorithm is exploited to perform multipath diversity combining in the blind mode, while a modified PN code timing recovery technique based on the timing error estimator extracts the finger error signals path by path independently. Taking the advantage of inherent diversity, this modified PN code timing recovery technique can efficiently combine finger error signals to avoid the problems with the drift or flutter effects in the timing error signals, and thus provide better code tracking performance as well. Extensive computer simulation results have verified the analysis and indicated very attractive performance of the proposed technique.

In this paper, we discuss a neural network approach for blind signal extraction of temporally correlated sources. Assuming autoregressive models of source signals, we propose a very simple neural network model and an efficient on-line adaptive algorithm that extract, from linear mixtures, a temporally correlated source with an arbitrary distribution, including a colored Gaussian source and a source with extremely low value (or even zero) of kurtosis. We then combine these extraction processing units with deflation processing units to extract such sources sequentially in a cascade fashion. Theory and simulations show that the proposed neural network successfully extracts all arbitrarily distributed, but temporally correlated source signals from linear mixtures.

In this paper we propose a new pipelined architecture for the LMS adaptive filter which can be implemented with less than half the amount of calculation needed for the conventional architectures. Even though the proposed architecture reduces the required calculation, it can simultaneously produce good convergence characteristics, a short latency and high throughput characteristics.

This paper proposes adaptive line enhancers with new coefficient update algorithms on the basis of least-square-error criteria. Adaptive algorithms by least-squares are known to converge faster than stochastic-gradient ones. However they have high computational complexity due to matrix inversion. To avoid matrix inversion the proposed algorithms adapt only one coefficient to detect one sinusoid. Both FIR and IIR types of adaptive algorithm are presented, and the techniques to reduce the influence of additive noise is described in this paper. The proposed adaptive line enhancers have simple structures and show excellent convergence characteristics. While the convergence of gradient-based algorithms largely depend on their stepsize parameters, the proposed ones are free from them.

In this paper, we propose a new structure of blind equalizer and its cost function. The proposed cost function is a quadratic form and has the unique solution. In addition, the proposed scheme can employ iterative algorithms which achieve less computational complexity and can be easily realized in real time processing. In order to verify the effectiveness of the proposed schemes, several computer simulations including a 64-QAM signal equalization have been shown.

This paper proposes an adaptive noise canceller with low signal-distortion in the presence of crosstalk. The proposed noise canceller has two pairs of cross-coupled adaptive filters, each of which consists of the main filter and a sub filter. The signal-to-noise ratios (SNRs) of the primary and the reference signals are estimated by the sub filters. To reduce signal distortion at the output of the adaptive noise canceller, the step sizes for coefficient adaptation in the main filters are controlled according to the estimated SNRs. Computer simulation results show that the proposed noise canceller reduces signal distortion in the output signal by up to 15 dB compared to the conventional noise canceller.

Classification of the new and used bills using the spectral patterns of raw time-series acoustic data (observation data) poses some difficulty. This is the fact that the observation data include not only a bill sound, but also some motor sound and noise by a transaction machine. We have already reported the method using adaptive digital filters (ADFs) to eliminate the motor sound and noise. In this paper, we propose an advanced technique to eliminate it by the neural networks (NNs). Only a bill sound is extracted from observation data using prediction ability of the NNs. Classification processing of the new and used bills is performed by using the spectral data obtained from the result of the ADFs and the NNs. Effectiveness of the proposed method using the NNs is illustrated in comparison with former results using ADFs.

In this paper, comparison of various orthogonal transforms in Wiener filtering is discussed. The study involves the family of discrete orthogonal transforms called Complex Hadamard Transform, which has been recently introduced by the same authors. Basic definitions, properties and transformation kernel of Complex Hadamard Transform are also shown.

In this paper, a new gradient-based adaptive algorithm for the estimation of discrete Fourier coefficients (DFC) of a noisy sinusoidal signal is proposed based on a summed least mean squared error criterion. This algorithm requires exactly the same number of multiplications as the conventional LMS algorithm, and presents much improved performance in both white and colored noise environments at the expense of some additional memories and additions only. We first analyze the performance of the conventional LMS algorithm in colored additive noise, and point out when its performance deteriorates. Then, a summed least mean squared error criterion is proposed, which leads to the above-mentioned new gradient-based adaptive algorithm. The performance of the proposed algorithm is also analyzed for a single frequency case. Simulation results are provided to support the analytical findings and the superiority of the new algorithm.

This paper investigates a new class of pulse compression codes in which the phase rotates clockwise, and afterward, rotates anticlockwise (or rotates anticlockwise, and afterward, rotates clockwise). The spectrum energy then concentrates to the narrower band compared to the conventional code such as the Barker code and the pulse is compressed not to the width of a single subpulses, but to the width made by a collection of several subpulses. It is revealed that, using the new code, PSL (Peak Sidelobe Level) can be reduced to -25.6 dB (1/19) -25.1 dB (1/18), which is much smaller than using the Barker code and Frank code, when the compression ratio is about 10 or larger. Furthermore, the signal-to-noise ratio after compression, the appropriate IF bandwidth and Doppler tolerance for the new code are estimated by simulation.

In this paper, we propose an adaptive encoding method of fixed codebook in CELP coders and implement an adaptive fixed code-excited linear prediction (AF-CELP) speech coder as a low-bit-rate extension to the 8 kbit/s CS-ACELP. The AF-CELP can be implemented at low bit rates as well as low complexity by exploiting the fact that the fixed codebook contribution to the speech signal is periodic, as is the adaptive codebook (or pitch filter) contribution. Listening tests show that the 6.4 kbit/s AF-CELP has a comparable quality to the 8 kbit/s CS-ACELP under real environmental test conditions.