Mahoki Onoda

Robust two dimensional spectral estimation based on AR model excited by a t-distribution process

A new robust two dimensional (2-D) spectral estimation method based on an AR model is proposed. The optimal coefficient is selected by assuming that the excitation signal is a t-distribution t(/spl alpha/) with /spl alpha/ degrees of freedom. When /spl alpha/=/spl infin/, we get the conventional least square (L/sub 2/) method. Thus, the proposed method can be regarded as a generalization of the L/sub 2/ method. Simulation results show that the obtained estimates using the proposed method with small /spl alpha/ are more efficient, the standard deviation (SD) of the estimation results are smaller, and more accurate than that with large /spl alpha/. The proposed estimator with small /spl alpha/ is more efficient and more accurate than the recursive method based on Hubers (1981) M-estimate.

Robust recursive spectral estimation based on AR model excited by a t-distribution process

In this paper a new robust spectral estimation method based on an AR model is proposed. The optimal coefficient is selected by assuming that the excitation signal is t-distribution t(/spl alpha/) with /spl alpha/ degrees of freedom. The calculation is done by using a recursive algorithm. When /spl alpha/=/spl infin/, we get the RLS method. Simulation results show that the obtained estimates using the proposed method with small /spl alpha/ are more efficient, the standard deviation (SD) of the estimation results are smaller, and more accurate than that with large /spl alpha/. The proposed estimator with small /spl alpha/ is more efficient and more accurate then the recursive method based on Hubers M-estimate.<<ETX>>

Spectral estimation based on AR-model excited by t-distribution process

A new spectral estimation method is proposed. Since in the least square L/sub 2/ method the obtained estimates are very much affected by the large signal portions, in the proposed method a loss function which assigns large weighting factor for the small residual portions and vice versa is used. The loss function is based on an assumption that the residual signal has an identical and independent t-distribution t( alpha ) with alpha degrees of freedom to achieve accurate and efficient (low standard deviation) estimates. When alpha = infinity , the conventional L/sub 2/ method is obtained. In the calculation, the loss function is modified in a way similar to the autocorrelation method, so that the proposed method can be seen as a generalization of the autocorrelation method. The optimal solution is selected by the Newton-Raphson method. The simulation results show that only a few iterations are needed to reach a stationary point, the stationary point is always a local minimum, and the obtained predictor is stable.<<ETX>>

Robust recursive time series modeling based on an AR model excited by a t-distribution process

In this correspondence, a new robust recursive spectral estimation based on an AR model is proposed. The optimal coefficients are selected by assuming that the excitation signal has a t-distribution t(/spl alpha/) with /spl alpha/ degrees of freedom. With /spl alpha/=/spl infin/, we get the RLS method. Simulation results show that the obtained estimates using the proposed method with small /spl alpha/ are more efficient, and the standard deviation (SD) of the estimation results is smaller and more accurate than that with large /spl alpha/. The proposed estimator with small /spl alpha/ is also more efficient and more accurate than the recursive method based on Hubers M estimate. Two approaches are used, i.e., the infinite memory and the exponentially weighted approaches.

A distributed reconfiguration controller for linear array harvest problem: hierarchically quasi-normalized neural approach

WSI is considered liable to have several faults at the beginning of the production stage and during its operating lifetime. This paper describes a design of distributed controller for reconfiguration on harvesting linear array system as a degradable system with assumption that not only basic cells but also the connection links are subject to fault condition. An inherently distributed feature of a new class of cellular neural network is used in hierarchical method. The proposed method is a simple heuristic distributed process with cellular (next neighbor) information. It has simple structures that have minimum penalty in WSI area thus minimizing the reliability cost.<<ETX>>

Logical function and delay time extraction from MOS circuit data

An algorithm to extract logical function and delay-time from CMOS circuit-level data is proposed. The resultant data from this algorithm is a logic-level circuit description. It is applied to conventional logic simulators. As a result, a large circuit can be simulated at once, and the time needed for simulation and verification is saved. The algorithm consists of three parts, network partitioning, extraction of logical function, and extraction of delay time.<<ETX>>

A compact video delay line

An improved design of distributed parameter video delay line is discussed in which small size is achieved with better frequency and time domain characteristics. The device consists of the tandem connection of unit sections each of which is a distributed delay line of proper length using ferrite cores both inside and outside of the coil. This construction permits larger diameter of delay line with improved transfer characteristics, and consequently larger time delay can be obtained in shorter length. The experimental results show that a 1 μS delay line with 3 Mc bandwidth is constructed for about 2 inch length with little waveform distortion.