Informatica

This paper addresses the study of the speech intelligibility enhancement. The speech model, noise sources, perceptual aspects of speech, and performance evaluation are reviewed. The intelligibility enhancement system based on spectral subtraction technique is investigated. Spectral density estimation device based on the algorithm of smoothed periodograms is analysed. Determination of the silence intervals, efficiency of the silence intervals determination, and signal to noise ratio evaluation are discussed. Speech intelligibility enhancement device is described.

In this paper we show that the least mean square (LMS) algorithm can be speeded up without changing any of its adaptive characteristics. The parallel LMS adaptive filtering algorithm and its modifications are presented. High speed is achieved by increasing the parallelism in the LMS adaptive algorithm through a proper modification of the LMS adaptive algorithm. An iterative procedures for efficient computation of the lower triangular inverse matrix and the input signal covariance matrix are presented.

Statistical properties are examined for a class of pipelined-block linear time-varying (LTV) and linear time-invariant (LTI) discrete-time systems. Pipelined-block equations are derived, using the general solution of LTV discrete-time system in state space. Afterwards, we analysed the state covariance and output covariance matrices of pipelined-block LTV and LTI discrete-time systems in state space. For this class of pipelined-block realizations expressions are found for calculation of characteristics of the roundoff noise. Finally, scaling in the pipelined LTV discrete-time systems in state space is considered.

For pipelining and block processing in linear time-varying (LTV), linear periodically time-varying (LPTV), and linear time-invariant (LTI) discrete-time systems, we suggest to use the general solution of state space equations. First, we develop three pipelined-block models for LTV, LPTV, and LTI discrete-time systems, and two pipelined-block structures. Afterwards, we analyse complete state controllability, complete output controllability, and complete observability of LTV and LTI pipelined-block discrete-time systems.

In this paper, we propose to present the direct form recursive digital filter as a state space filter. Then, we apply a look-ahead technique and derive a pipelined equation for block output computation. In addition, we study the stability and multiplication complexity of the proposed pipelined-block implementation and compare with complexities of other methods. An algorithm is derived for the iterative computation of pipelined-block matrices.

Two-dimensional signals of physical phenomena may be inadvertently altered before recording through the system whose bandwidth is smaller than that of the signal. It is often desired to restore later such data by removing the effects of the linear system. This restoration may be accomplished by synthesizing two-dimensional (2-D) inverse filters on computers. Approximations are necessary to insure the stability of the inverse filter.

The input–output relationship of the periodically time-varying (PTV) systems, impulse response of the PTV state–space system, and the transfer function of the PTV system are presented. A coefficient sensitivity is investigated by using a virtual PTV state-space system in which periodically time-varying coefficients are stochastically varied.

The aim of this paper is to concentrate in one place and to show the relations among the matrix block impulse response, block impulse response, matrix impulse response and impulse response of linear time-varying (LTV) systems, frozen-time LTV systems, linear periodically time-varying (LPTV) systems, and linear time-invariant (LTI) systems.

This paper discusses the inversion of linear periodically time-varying (LPTV) digital filters using the idea of converting the LPTV filter to the block time-invariant filter. Explicit expressions are given to determine the inversion of LPTV filters. Controllability, observability and stability of the inversion of LPTV filters are discussed.