A method for estimating sound source distance in dynamic auditory „scenes‟ using binaural data is presented. The technique requires little prior knowledge of the acoustic environment. It consists of feature extraction for two dynamic distance cues, motion parallax and acoustic τ, coupled with an inference framework for distance estimation. Sequential and nonsequential models are evaluated using...

In Classical Hypothesis testing volumes of data is to be collected and then the conclusions are drawn which may take more time. But, Sequential Analysis of statistical science could be adopted in order to decide upon the reliable / unreliable of the developed software very quickly. The procedure adopted for this is, Sequential Probability Ratio Test (SPRT). In the present paper, we have propose...

The reliability and the cost of electronic circuits are closely connected to the maximum power dissipated by them. Tools for evaluating the worst case power consumption of sequential circuits is becoming a primal concern for designers of low-power circuits. In the paper the task of estimation of peak sustainable power for CMOS synchronous sequential circuit is considered when its automaton desc...

In this report the problem of sequential detection and estimation of change-points is considered. The sense of this problem is as follows: in practice after raising an alarm signal about a change it is often required to divide the whole obtained sequential sample into subsamples of observations before and after an unknown change-point. In this report asymptotically optimal methods are proposed ...

We consider the problem of density estimation when the data is in the form of a continuous stream with no fixed length. In this setting, implementations of the usual methods of density estimation such as kernel density estimation are problematic. We propose a method of density estimation for massive datasets that is based upon taking the derivative of a smooth curve that has been fit through a ...

A new sequential method for the regression problems is studied. The suggested method is motivated by boosting methods in the classification problems. Boosting algorithms use the weighted data to update the estimator. In this paper we construct a sequential estimation method from the viewpoint of nonparametric estimation by using mixture distribution. The algorithm uses the weighted residuals of...

The aim is to compare and contrast the stability of the estimation method based on the embedding of the estimation problem into an optimally posed two-point boundary value problem with that of the simultaneous method which is boundary value free and which imposes the discretization of the differential equation as a set of equality constraints. The embedding method leads to an unconstrained opti...