We consider the problem of estimating the parameters of a chirp signal observed in multiplicative noise, i.e., whose amplitude is randomly time-varying. Two methods for solving this problem are presented. First, an unstructured nonlinear least-squares approach (NLS) is proposed. It is shown that by minimizing the NLS criterion with respect to all samples of the time-varying amplitude, the probl...

The estimation and the compensation of particular amplitude distortions, affecting the consumer-grade receivers in broadband satellite communications, are considered. We present a novel estimator, analytically derived by exploiting low-order polynomial approximations of the equivalent distortion filter, which is modeled as an exponential function of the frequency. In the bandwidth of practical ...

4.35k1.86 15.48f3.21 Abstract Previous research showed that whitening the surface electromyogram (EMC) can improve EMG amplitude estimation. However, conventional linear-filter whitening fails at low EMG amplitude levels, perhaps due to additive background noise in the measured EMG signal. This paper describes an adaptive whitening technique, effective at low EMG levels, that cascades a non-ada...

Probability theory is applied to the problem of estimating the amplitudes of the sinusoids in nuclear magnetic resonance data containing two exponentially decaying sinusoids. The posterior probability-density of one of the amplitudes is derived independent of the phases, frequencies, decay-rate constants, variance of the noise, and the amplitude of the other sinusoid. This probability-density f...

OBJECTIVE A method for conduction block (CB) estimation, based on compound muscle action potentials (CMAP) elicited by stimulation at sites proximal and distal to the region in which a block is suspected, which is less sensitive to temporal dispersion than methods based on area and amplitude estimation, routinely used in clinical practice. METHODS The method is based on deconvolution of CMAPs...

The learning process for multi layered neural networks with many nodes makes heavy demands on computational resources. In some neural network models, the learning formulas, such as the Widrow-Hoff formula, do not change the eigenvectors of the weight matrix while flatting the eigenvalues. In infinity, this iterative formulas result in terms formed by the principal components of the weight matri...

Recently we find several candidates of quantum algorithms that may be implementable in near-term devices for estimating the amplitude a given state, which is core sub- routine various computing tasks such as Monte Carlo methods. One those based on maximum likelihood estimate with parallelized circuits. In this paper, extend method so it incorporates realistic noise effect, and then give an expe...