Two-band speech model which assumes lower band is a quasi-periodic component and upper band is a non-periodic component is widely used due to its natural and simple framework. In this paper, a score function is defined for splitting lower and upper band of two-band speech model and estimation method of band-splitting frequency which is the boundary of the two bands is proposed. The score functi...

Recently, speech researchers have begun to base spectral analyses of sibilant fricatives on modern spectral estimators that promise reduced error in the estimation of the spectrum of the acoustic waveform. In this paper we look at the effect that the choice of spectral estimator has on the estimation of spectral properties of English voiceless sibilant fricatives.

A number of recent works have proposed to solve the line spectral estimation problem by applying off-the-grid extensions of sparse estimation techniques. These methods are preferable over classical line spectral estimation algorithms because they inherently estimate the model order. However, they all have computation times which grow at least cubically in the problem size, thus limiting their p...

In the next three lectures, we aim to study techniques used to estimate the power spectrum of random processes. We consider a discrete-time model, where we are given a discrete-time sequence of zero mean random variables { y(t) , t = 0,±1,±2, . . . } which are assumed to be the output of a second-order stationary random process, sampled at integral multiples of the sampling period Ts = 1/Fs whe...

This paper provides a framework for estimating parameters in a wide class of dynamic rational expectations models. The framework recognizes that dynamic RE models are often meant to match the data only in limited ways. In particular, interest may focus on a subset of frequencies. Thus, this paper designs a frequency domain version of GMM. The estimator has several advantages over traditional GM...

Omid S. Jahromi, Bru e A. Fran is, Raymond H. Kwong Systems Control Group, Department of Ele tri al and Computer Engineering, University of Toronto Toronto, ON, M5S 3G4 Canada fomidj, fran is, kwongg ontrol.toronto.edu ABSTRACT This arti le introdu es a mathemati al theory for estimating the power spe tral density (PSD) of a random signal based on low-sampling-rate measurements. We formulate th...

Attenuation estimation methods for medical ultrasound are important because attenuation properties of soft tissue can be used to distinguish between benign and malignant tumors and to detect diffuse disease. The classical spectral shift method and the spectral difference method are the most commonly used methods for the estimation of the attenuation; however, they both have specific limitations...

The advanced network applications enable software driven spectral analysis of non-stationary signal or processes which precisely involves domain analysis with the purpose of decomposing a complex signal coefficients into simpler forms. However, the proper estimation of power coefficients over frequency components of a random signal leads to provide very useful information required in various fi...

he power spectrum reveals the existence, or the absence, of repetitive patterns and correlation structures in a signal process. These structural patterns are important in a wide range of applications such as data forecasting, signal coding, signal detection, radar, pattern recognition, and decision-making systems. The most common method of spectral estimation is based on the fast Fourier transf...