This paper presents an analysis-by-synthesis multimode harmonic coder (AbS-MHC) that employs new techniques to improve both the speech model accuracy and the parameter estimation robustness in the low rate harmonic coding framework. To improve the speech model accuracy, an enhanced frequency domain transition model is used in conjunction with the sinusoidal model based harmonic coding of voiced...

An important problem in speech coding framework is model parameters estimation. In most cases parametric speech coding methods do not preserve shape of speech waveform. This fact implies straightforward parameters estimation and analysisby-synthesis method is hardly used. A novel analysis-by-synthesis parameters estimation method in speech coders based on harmonic models presented. We introduce...

In recent years, active filters have been considered and developed for elimation of harmonics in power networks. Comparing with passive, they are smaller and have better compensating characteristics and resistance to line distortions. In this paper, a novel idea based on adaptive filter theory in presented to develop an active filter to eliminate the distortions of an arbitrary signal. Using th...

We present a Bayesian analysis method that estimates the harmonic structure of musical instruments in music signals on the basis of psychoacoustic evidence. Since the main objective of multipitch analysis is joint estimation of the fundamental frequencies and their harmonic structures, the performance of harmonic structure estimation significantly affects fundamental frequency estimation accura...

This paper presents a new system-wide harmonic state estimation method with the capability to identify harmonic sources with fewer meters than state variables. Note there are only a few simultaneous harmonic sources among the suspicious buses. By extending the concept of observability, the underdetermined system can be observable when considering the sparsity of harmonic sources. We formulate h...

In recent years, active filters have been considered and developed for elimation of harmonics in power networks. Comparing with passive, they are smaller and have better compensating characteristics and resistance to line distortions. In this paper, a novel idea based on adaptive filter theory in presented to develop an active filter to eliminate the distortions of an arbitrary signal. Using th...

The paper presents a new approach for the estimation of harmonic components of a power system using a linear adaptive neuron called Adaline. The learning parameters in the proposed neural estimation algorithm are adjusted to force the error between the actual and desired outputs to satisfy a stable difference error equation. The estimator tracks the Fourier coefficients of the signal data corru...

An algorithm for harmonic decomposition of time-variant signals is derived from a least squares harmonic (LSH) technique. The estimates of harmonic amplitudes and phases are formulated as the solution of a set of linear equations which minimizing mean square error; the signal frequency is modeled by a linear or quadratic polynomial and obtained via a local search over polynomial coefficients. A...

Estimating the fundamental frequency and harmonic parameters is basic for signal modeling in a power supply system. This paper presents a complexity-reduced algorithm for signal reconstruction in the time domain from irregularly spaced sampling values. Differing from the existing parameter estimation algorithms, either in power quality monitoring or in harmonic compensation, the proposed algori...