This paper proposes two novel Multi-bit Delta-Sigma Modulator (Δ Σ M) architectures based on a Dual-Quantization architecture. By using multi-bit quantization with single-bit feedback, Both eliminate the need for a multi-bit digital-to-analog converter (DAC) in the feedback loop. The first is a Digital quantization-Error Canceling Multi-bit (DECM)-Δ Σ M architecture that is able to achieve high resolution at a low oversampling ratio (OSR) because, by adjusting the coefficients of both analog and digital circuits, it is able to cancel completely the quantization error injected into the single-bit quantizer. Simulation results show that a signal-to-quantization-noise ratio of 90 dB is obtained with 3rd order 5-bit quantization DECM-Δ Σ M at an OSR of 32. The second architecture, an analog-to-digital mixed (ADM)-Δ Σ M architecture, uses digital integrators in place of the analog integrator circuits used in the Δ Σ M. This architecture reduces both die area and power dissipation. We estimate that a (2+2)-th order ADM-Δ Σ M with two analog-integrators and two digital-integrators will reduce the area of a 4-th order Δ Σ M by 15%.

For evaluating the output response fluctuation of the actual environmental acoustic system excited by arbitrary random inputs, it is important to predict a whole probability distribution form closely connected with many noise evaluation indexes Lx, Leq and so on. In this paper, a new type evaluation method is proposed by introducing lower and higher order type functional models matched to the prediction of the response probability distribution form especially from a problem-oriented viewpoint. Because of the non-negative property of the sound intensity variable, the response probability density function can be reasonably expressed in advance theoretically by a statistical Laguerre expansion series form. The system characteristic between input and output can be described by the regression relationship between the distribution parameters (containing expansion coefficients of this expression) and the stochastic input. These regression functions can be expressed in terms of the orthogonal series expansion. Since, in the actual environment, the observed output is inevitably contaminated by the background noise, the above regression functions can not be directly employed as the models for the actual environment. Fortunately, the observed output can be given by the sum of the system output and the background noise on the basis of additivity of intensity quantity and the statistical moments of the background noise can be obtained in advance. So, the models relating the regression functions to the function of the observed output can be derived. Next, the parameters of the regression functions are determined based on the least-squares error criteria and the measure of statistical independency according to the level of non-Gaussian property of the function of the observed output. Thus, by using the regression functions obtained by the proposed identification method, the probability distribution of the output reducing the background noise can be predicted. Finally, the effectiveness of the proposed method is confirmed experimentally too by applying it to an actual indoor-outdoor acoustic system.

The distribution for the envelope of the received signal over frequency-nonselective slow fading channels with additive white Gaussian noise (AWGN) is derived in this paper. System performances of noncoherent M-ary signals over slow and flat fading channels in the presence of AWGN can be evaluated from the new probability density function (PDF) of the envelope.

Recently, in the modem, the spread spectrum communication system and the software radio, Digital Signal Processor type Squaring Loop (DSP-squaring-loop) is employed in the demodulation of Binary Phase Shift Keying (BPSK) signal. The DSP-squaring-loop extracts the carrier signal that is used for the coherent detection. However, in case the Signal to Noise Ratio (SNR) is low, the DSP-Phase Locked Loop (DSP-PLL) can not pull in the frequency offset and the phase offset. In this paper, we propose a DSP-squaring-loop that is robust against noise and which uses the adaptive notch filter type frequency estimator and the adaptive Band Pass Filter (BPF). The proposed method can extract the carrier signal in the low SNR environment. The effectiveness of the proposed method is confirmed by the computer simulation results.

This paper deals with a study of a problem for finding the minimum-cost spanning tree with a response-time bound. The relation of cost and response-time is given as a monotonous decreasing and convex function. Regarding communication bandwidth as cost in an information network, this problem means a minimum-cost tree shaped routing for response-time constrained broadcasting, where any response-time from a root vertex to other vertex is less than a given time bound. This problem is proven to be NP-hard and consists of the minimum-cost assignment to a rooted tree and the minimum-cost tree finding. A nonlinear programming algorithm solves the former problem for the globally optimal solution. For the latter problem, different types of heuristic algorithms evaluate to find a near optimal solution experimentally.

In this report, a design method of neural networks for limit cycle generator is described. First, the constraint conditions for the synaptic weights, which are given by the linear inequalities, are derived from the dynamics of neural networks. Next, the linear inequalities are solved by the linear programming method. The synaptic weights and other parameters are determined by the above solutions. Furthermore, neuro-based limit cycle generator is designed with analog electronic circuits and simulated by Spice. Finally, we confirm that our design method is efficient and practical for the design of neuro-based limit cycle generator.

In this paper we propose a new simplified algorithm for cascaded second order adaptive notch filters implemented using an allpass filter, for elimination of multiple sinusoids. Each of the stages of the notch filter is implemented using direct form second order allpass filter. We also present an analysis which compares the proposed algorithm with the conventional simplified algorithm, and which indicates that the proposed algorithm has a reduced bias in the estimation of the multiple input sinusoids. Simulation results that have been provided confirm this analysis.

This paper deals with the problem of autoregressive (AR) spectral estimation from a finite set of noisy observations without a priori knowledge of additive noise power. A joint technique is proposed based on the high-order and true-order AR model fitting to the observed noisy process. The first approach utilizes the uncompensated lattice filter algorithm to estimate the parameters of the over-fitted AR model and is one-pass. The latter uses the noise compensated low-order Yule-Walker (LOYW) equations to estimate the true-order AR model parameters and is iterative. The desired AR parameters, equivalently the roots, are extracted from the over-fitted model roots using a root matching technique that utilizes the results obtained from the second approach. This method is highly accurate and is particularly suitable for cases where the system of unknown equations are strongly nonlinear at low SNR and uniqueness of solution from the LOYW equations cannot be guaranteed. In addition, fuzzy logic is adopted for calculating the step size adaptively with the cost function to reduce the computational time of the iterative total search technique. Several numerical examples are presented to evaluate the performance of the proposed scheme in this paper.

A current-mode folding and interpolating analog to digital converter (ADC) architecture with multiplied folding amplifiers is proposed in this paper. A current-mode multiplied folding amplifier is employed not only to reduce the number of reference current source, but also to decrease a power dissipation within the ADC. The proposed ADC for 12 bit was designed by a 0.65 µm n-well CMOS single poly/double metal process. The simulated result shows a differential nonlinearity (DNL) of 0.5LSB, an integral nonlinearity (INL) of 1.0LSB, 20 Ms/s of the data conversion rate, and the power dissipation of 180 mW with a power supply of 5 V.

A merged analog-digital circuit architecture is proposed for implementing intelligence in SoC systems. Pulse modulation signals are introduced for time-domain massively parallel analog signal processing, and also for interfacing analog and digital worlds naturally within the SoC VLSI chip. Principles and applications of pulse-domain linear arithmetic processing are explored, and the results are expanded to the nonlinear signal processing, including an arbitrary chaos generation and continuous-time dynamical systems with nonlinear oscillation. Silicon implementations of the circuits employing the proposed architecture are fully described.

This paper proposes a new hybrid active noise control (ANC) system without the estimation of the secondary path filter in advance. The algorithm of the feedforward part of the proposed method is based on the simultaneous equations method and the feedback part employs the filtered-X LMS algorithm. The estimation of the secondary path filter is obtained in the operation of the feedforward part and it is used in the feedback part. When the secondary path changes in the operation of the system, the proposed system can follow to this change. In the simulation example which treats the colored measurement noise, the fine noise reduction performance is obtained.

The processes observed in a sound environment inevitably contain additional external noise of arbitrary distribution. Furthermore, the actual sound environment system exhibits various types of linear and non-linear characteristics, and it often contains an unknown structure. In this paper, a method for estimating the input signal for a sound environment system with unknown structure and additive noise of arbitrary probability distribution is proposed by introducing a system model of the conditional probability type. The effectiveness of the proposed theoretical method is confirmed experimentally by applying it to the actual problem of input estimation of the sound environment.

In this paper, a new expression is derived for the bit error rate (BER) performance of Gray-encoded MDPSK for M=2 and 4 in orthogonal frequency division multiplexing (OFDM) systems over time-variant and frequency-selective Rayleigh fading channels. We assume that the guard time is sufficiently larger than the delay spread to solve the intersymbol interference (ISI) problem on the demodulated OFDM signal. In this case, the performance depends on the Doppler spread of fading channel. The closed form expression for the bit error probability of MDPSK/OFDM extended from the result in [5] shows that the BER performance of MDPSK is determined by (N + NG ) fD Ts where N is the number of subchannels, NG the length of the guard interval, fD the maximum Doppler frequency, and Ts the sampling period. The theoretical analysis results are confirmed by computer simulations for DPSK and QDPSK signals.

Improvement of direct sequence spread spectrum (DSSS) communication systems' performance using a lattice based adaptive infinite impulse response (IIR) notch filter with a simplified adaptation algorithm is presented. The improvement is shown to be achieved by rejection of a narrowband interference in a received DSSS binary phase shift keying (BPSK) signal. Sources of noise generated by an adaptive IIR notch filter are also studied. Apart from noise associated with input additive white gaussian noise, noise attributed to leakage sinusoids due to fluctuation of steady-state variable coefficient is also analysed. Using statistical properties of notch filter and pseudonoise (PN) correlator outputs, improvement of the performance of a DSSS system gained by the use of interference rejection filter is shown. Computer simulation results are used to confirm analytically derived expressions.

A new adaptive multichannel filtering approach is introduced and analyzed in this paper. The technique is simpler and more appropriate than traditional approaches that have been addressed by means of groupwise vector ordering information. These filters are a two-stage filters based on rational functions (RF) using fuzzy transformations of the Euclidean and angular distances among the different vectors to adapt to local data in the color image. The output is the result of vector rational operation taking into account three fuzzy sub-function outputs. Simulation studies indicate that the filters are computationally attractive and have excellent performance such as edge and details preservation and accurate chromaticity estimation.

This paper proposes a new adaptation-mode control (AMC) for a robust adaptive microphone array with an adaptive blocking matrix (RAMA-ABM). The proposed AMC is based on cross correlations of two microphone signals and uses a state machine for controlling the adaptation to avoid target-signal cancellation. Evaluation with sound data obtained in different acoustic environments demonstrates that the noise reduction by the proposed AMC is 3 dB better than that by the AMC based on the SNR estimate. Subjective listening tests show that the quality of the output signal by the proposed AMC is comparable to or even better than those by the conventional AMCs.

In this letter, we introduce new parameters for classifying digitally modulated unknown QAM and PSK signals. Our two parameters for the classification are the variance of magnitude ratios and the mean of mod 2π phase differences. The gain adjustments of amplitudes are not required for the classification. Five different types of QAM constellations and three different types of PSK constellations are tested and the characteristics of our classification parameters are investigated in various SNR environments. Simulation results demonstrate the effectiveness of our proposed technique.

The application of an active noise control system in a finite-length duct is studied. Previously proposed single-input-single-output systems are inappropriate in this case, because reflection at the terminals degrades the performance, and/or infinite-impulse-response filters are required for perfect noise cancellation. In this paper, we propose a single-input-single-output system applicable to finite-length ducts, which theoretically achieves perfect noise cancellation while using finite-impulse-response filters only. The tap lengths of the filters are as short as the delays between the reference sensor and the secondary source. A useful implementation of the proposed system is also discussed.

The paper proposes a transmitter diversity scheme with a desired signal selection for the mobile communication systems in which the severe cochannel interference (CCI) is assumed to occur at the base station. The feature of the proposed scheme is that the criterion of the downlink branch selection is based on the desired signal power estimated by the correlation between the received signal and the unique word at the matched filter. Moreover, the unique word length control method according to the instantaneous SIR is applied to the proposed scheme, taking account of the uplink transmission efficiency. Computer simulation results show that the proposed scheme provides the better performance than the conventional transmitter diversity in the severe CCI environments, and that the unique word length control method applied to the proposed scheme decreases the unique word length without the degradation of the transmission quality, comparing with the fixed unique word length method.

While spatial reuse in a high-speed ring increases the throughput performance, it leads to a fairness problem in distributing the network bandwidth among distinct nodes. To alleviate this problem, fairness control algorithms based on a packet window have been developed. Under these algorithms, satisfied nodes are forced to pass empty slots to starved downstream nodes until their windows are refilled by a reset signal. This regulation incurs a bandwidth waste corresponding to the travel distance of those empty slots. In this paper, a waste-free fairness control method based on a two-layer window composed of the cycle and packet windows is developed. Using the proposed method, packets allocated to multiple fairness cycles are simultaneously transferred and, in consequence, the otherwise wasted bandwidth can be reused to carry, in advance, packets allocated to future fairness cycles. This method is applied to two typical ring protocols with only the packet window, ATMR and MetaRing, and their performances are investigated. The simulation results show that the cycle window is very effective to improve the performance of the ATMR and MetaRing protocols.