We report the experimental study of the thermionic emission of electrons into overbarrier states of a superlattice, tailored to enhance electron confinement within a closely spaced quantum well. Partial suppression of the thermionic current is observed at room temperature. A critical evaluation of the practical applications of the effect is offered. Furthermore, the tunnel injection into partially delocalized Stark states of the superlattice is observed at low temperature.

Enhanced confinement of electrons at room temperature using a superlattice reflector

In this paper, we discuss a pre-inverse adaptive system in which the adaptive filter is located before the unknown system. We then propose an adaptive system that does not require a replica of the unknown system, as in the case of the filtered-x adaptive system. With the proposed method, we can therefore avoid the instability that arises from error in the replica of the unknown system. In the proposed method, the inverse transfer function of the minimum-phase part of the unknown system is estimated by an adaptive exponential filter. The inverse transfer function of the allpass part of the unknown system is estimated by an adaptive transversal filter, whose inverse can be easily realized by reversing the order of the weights. Finally, a numerical verification of the analytical results, the convergence performance of the adaptive systems, and a performance comparison with the filtered-x adaptive system are obtained by computer simulation

A Study on Pre-Inverse Adaptive System Based on Estimation of Minimum-Phase and Allpass Transfer Function

In order to lower the switching losses and harmonic ratio, improve the precision of the STATCOM in the same time, the adaptive inverse control based on PAM+PWM method is proposed in this paper. The combination of PAM+PWM method is presented to enable the system to achieve the quality of low switching losses and good harmonic elimination effect. Furthermore, considering the nonlinear and time-varying characteristics which are caused by the introduction of the PAM and PWM method, an adaptive inverse control method is designed to adjust the parameters of the nonlinear mathematic model constantly to improve the precision of the control system. The results of simulation show the correctness of the proposed method.

The Use of Adaptive Inverse Control in Cascade STATCOM Modulated by PAM+PWM

The logarithmic adaptive digital filter (ADF) estimates the unknown system in which the transfer function is represented by a rational function of z. It consists of an ADF to estimate the logarithm of the denominator polynomial of the transfer function and a transversal ADF to estimate the numerator polynomial. Compared to the conventional transversal ADF, it is known that the number of taps can be reduced in this kind of ADF.



Studies have been made concerning the adaptive algorithm of the logarithmic ADF and the convergence condition. A problem is that the correlation matrix is a function of the input and the output signals of ADF. This increases the convergence time, compared to the transversal ADF, when the input signal is white.



This paper discusses the method of the improvement of the convergence speed and proposes the adaptive algorithm for the logarithmic ADF based on the LMS/Newton method. The successive computation of the inverse matrix of the correlation matrix (Jacobian) as well as the adaptive algorithm are derived. In contrast to the algorithm for the transversal ADF, it is shown that the square term of the estimation error is included in the update term of the tap vector.



Finally, the convergence condition for the proposed algorithm is derived. The convergence speed, the adaptive algorithm and the convergence condition are examined by a computer simulation.

An adaptive algorithm of a logarithmic‐type adaptive digital filter based on the LMS/Newton method

In the traditional fast-Fourier trans form (FFT) algorithm, the design for high- speed operation is made based on the number of operations, especially the number of multiplications, which is time-consuming in the general-purpose processor. This is not necessarily reasonable in the digital signal processor (DSP), where the multiplication can be performed in the time equal to that of other operations. From such a viewpoint, this paper proposes an algorithm which matches the feature of DSP, where the pro cessing is fast when the multiply-accumulate operations are continued in execution. the algorithm is applicable when the number of data IV can be factorized into mutually prime factors. DFT for smaller number (factor) of data is modified into the cyclic convolution, and is executed at a high speed (small- N algorithm). the proposed algorithm is composed of the small-N algorithms and DFT for a large number of data (multidimensional algorithm), which combines small-N algorithms into a multidimensional DFT. the number of operations is not necessarily reduced in the proposed algorithm, compared with the traditional FFT, but it was verified by an actual run of the program on DSP that the execution time is reduced.

Naoki Mikami

Papers

An adaptive algorithm of a logarithmic‐type adaptive digital filter based on the LMS/Newton method

A new DSP-oriented FFT algorithm