Audio Analysis/synthesis System

A method and apparatus for the automatic analysis, synthesis and modification of audio signals, based on an overlap-add sinusoidal model, is disclosed. Automatic analysis of amplitude, frequency and phase parameters of the model is achieved using an analysis-by-synthesis procedure which incorporates successive approximation, yielding synthetic waveforms which are very good approximations to the original waveforms and are perceptually identical to the original sounds. A generalized overlap-add sinusoidal model is introduced which can modify audio signals without objectionable artifacts. In addition, a new approach to pitch-scale modification allows for the use of arbitrary spectral envelope estimates and addresses the problems of high-frequency loss and noise amplification encountered with prior art methods. The overlap-add synthesis method provides the ability to synthesize sounds with computational efficiency rivaling that of synthesis using the discrete short-time Fourier transform (DSTFT) while eliminating the modification artifacts associated with that method.Georgia Tech Research Corporatio

Enhancing the Instantaneous Dynamic Range of Electronic Warfare Receivers Using Statistical Signal Processing

Accurately processing multiple, time-coincident signals presents a challenge to Electronic Warfare (EW) receivers, especially if the signals are close in frequency and/or mismatched in amplitude. The metric that quantifies an EW receiver\u27s ability to measure time-coincident signals is the Instantaneous Dynamic Range (IDR), defined for a given frequency estimation accuracy, a given frequency separation and a given SNR as the maximum signal amplitude ratio that can be accommodated. Using a two sinusoid time-series model, this thesis analyzes IDR for ideal intercept and parametric digital EW receivers. In general, the number of signals contained in the EW receiver measurement interval is unknown. Thus, the non-parametric Discrete Fourier Transform (DFT) is employed in an EW intercept receiver with the associated amplitude dependent spectral leakage which limits IDR. A novel method to improve the DFT-based intercept receiver IDR by compensating for the high amplitude signal\u27s spectral leakage using computationally efficient 3 bin interpolation algorithms is proposed and analyzed. For a desired frequency estimation accuracy of 1.5 bins, the method achieves an IDR of 57 dB with little frequency separation dependence when the signals are separated by more than 2 bins with a low amplitude signal SNR of 10 dB. For situations where the number of signals contained in the measurement interval is known, the IDR of an Iterative Generalized Least Squares (IGLS) algorithm-based parametric receiver is analyzed. A real and complex signal IDR Cramer-Rao Bound (IDR-CRB) is derived for parametric receivers by extending results contained in Rife. For tight frequency estimate requirements (these requirements depend on the number of measurement samples), the IDR-CRB yields achievable bounds. For less stringent frequency estimate requirements, the IDR-CRB is unrealisti

Synchrophasor Assisted Efficient Fault Location Techniques In An Active Distribution Network

Reliability of an electrical system can be improved by an efficient fault location identification for the fast repair and remedial actions. This scenario changes when there are large penetrations of distributed generation (DG) which makes the distribution system an active distribution system. An efficient use of synchrophasors in the distribution network is studied with bidirectional power flow, harmonics and low angle difference consideration which are not prevalent in a transmission network. A synchrophasor estimation algorithm for the P class PMU is developed and applied to identify efficient fault location. A fault location technique using two ended synchronized measurement is derived from the principle of transmission line settings to work in a distribution network which is independent of line parameters. The distribution systems have less line length, harmonics and different sized line conductors, which affects the sensitivity of the synchronized measurements, Total Vector Error (TVE) and threshold for angular separation between different points in the network. A new signal processing method based on Discrete Fourier Transform (DFT) is utilized to work in a distribution network as specified in IEEE C37.118 (2011) standard for synchrophasor. A specific P and M classes of synchrophasor measurements are defined in the standard. A tradeoff between fast acting P class and detailed measurement M class is sought to work specifically in the distribution system settings which is subjected to large amount of penetrations from the renewable energy

Signal processing with Fourier analysis, novel algorithms and applications

Fourier analysis is the study of the way general functions may be represented or approximated by sums of simpler trigonometric functions, also analogously known as sinusoidal modeling. The original idea of Fourier had a profound impact on mathematical analysis, physics and engineering because it diagonalizes time-invariant convolution operators. In the past signal processing was a topic that stayed almost exclusively in electrical engineering, where only the experts could cancel noise, compress and reconstruct signals. Nowadays it is almost ubiquitous, as everyone now deals with modern digital signals. Medical imaging, wireless communications and power systems of the future will experience more data processing conditions and wider range of applications requirements than the systems of today. Such systems will require more powerful, efficient and flexible signal processing algorithms that are well designed to handle such needs. No matter how advanced our hardware technology becomes we will still need intelligent and efficient algorithms to address the growing demands in signal processing. In this thesis, we investigate novel techniques to solve a suite of four fundamental problems in signal processing that have a wide range of applications. The relevant equations, literature of signal processing applications, analysis and final numerical algorithms/methods to solve them using Fourier analysis are discussed for different applications in the electrical engineering/computer science. The first four chapters cover the following topics of central importance in the field of signal processing: • Fast Phasor Estimation using Adaptive Signal Processing (Chapter 2) • Frequency Estimation from Nonuniform Samples (Chapter 3) • 2D Polar and 3D Spherical Polar Nonuniform Discrete Fourier Transform (Chapter 4) • Robust 3D registration using Spherical Polar Discrete Fourier Transform and Spherical Harmonics (Chapter 5) Even though each of these four methods discussed may seem completely disparate, the underlying motivation for more efficient processing by exploiting the Fourier domain signal structure remains the same. The main contribution of this thesis is the innovation in the analysis, synthesis, discretization of certain well known problems like phasor estimation, frequency estimation, computations of a particular non-uniform Fourier transform and signal registration on the transformed domain. We conduct propositions and evaluations of certain applications relevant algorithms such as, frequency estimation algorithm using non-uniform sampling, polar and spherical polar Fourier transform. The techniques proposed are also useful in the field of computer vision and medical imaging. From a practical perspective, the proposed algorithms are shown to improve the existing solutions in the respective fields where they are applied/evaluated. The formulation and final proposition is shown to have a variety of benefits. Future work with potentials in medical imaging, directional wavelets, volume rendering, video/3D object classifications, high dimensional registration are also discussed in the final chapter. Finally, in the spirit of reproducible research we release the implementation of these algorithms to the public using Github

Power Harmonic Analysis Based on Continuously Adjustable Asymmetric Window

The study of harmonics signal analysis in electric power system is a classic and important research subject. The signal by using traditional Fourier transform methods are nearly truncated by constant coefficient symmetry window or asymmetric window. This paper propose the improved continuously adjustable asymmetric window for precise harmonic parameters measurement and the uniform formulas for calculating the parameters of harmonics and interharmonic is obtained by the asymmetric window-based phase difference correction method. The major advantages of this method is easy to implement and independent of window spectrum. The simulation analysis results proves that there is obvious high precision, effectiveness and universal applicability of this method

Separation of musical sources and structure from single-channel polyphonic recordings

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Phase estimation in a navigation receiver

Tässä lisensiaatintutkimuksessa esitetään menetelmä näytteistetyn sinimuotoisen signaalin vaiheen estimointiin silloin, kun taajuus on tunnettu. Menetelmän nimi on vaihekorjattu korrelaatio (PCC) ja sillä voi estimoida vaiheen myös niissä tapauksissa, joissa signaalista ei ole kokonaisluvullista määrää jaksoja mittausvälissä. PCC-vaihe-estimaatin suorituskykyä tutkitaan vertaamalla sen neliösummavirhettä (MSE) Cramér-Rao alarajaan (CRLB). Jotta menetelmän analysointi ja vertailu läheisten menetelmien kanssa olisi helpompaa, signaalimallina on yksi sinimuotoinen signaali valkoisessa Gaussisessa kohinassa. Työssä esitetään lisäksi kaksi menetelmää häiriöisen signaalin vaihe-estimaatin neliösummavirheen pienentämiseen. Tyypillisiä häiriölähteitä ovat salamat ja läheisellä taajuudella toimivat lähettimet; menetelmät ovat vastaavasti nimeltään purskehäiriöiden poisto ja virheellisten ositteiden poisto. PCC-taajuusestimaatti saadaan seuraamalla signaalin vaiheen muuttumista peräkkäisissä mittausväleissä ja sen suorituskykyä sekä laskentakuormaa verrataan Interpoloituun DFT:hen (IDFT). Menetelmän sovellusalue on meteorologinen luotausjärjestelmä, joka käyttää VLF-navigointiverkkoja yläilmakehän tuulenmittaukseen. Estimointiongelmana on arvioida Doppler-ilmiön aiheuttama pienenpieni taajuussiirtymä. Venäläisen Alpharadionavigointiverkon lähetystaajuudet ovat erityisen haasteellisia, koska käytetyssä 400 ms:n mittausvälissä ei ole kokonaisluvullista määrää signaalin jaksoja. Useimmat taajuuden- ja vaiheenestimointimenetelmät eivät ole soveliaita tähän estimointiongelmaan. IDFT saattaisi olla käyttökelpoinen ja siksi sitä on käytetty vertailukohtana. Tietokonesimulaatioin osoitetaan, että vaihe-estimaatin MSE on lähellä CRLB:tä. Sama koskee taajuusestimaatteja, jotka on saatu seuraamalla signaalin vaiheen muuttumista peräkkäisissä mittausväleissä. Simulaatiot osoittavat myös, että PCC-taajuusestimaatin MSE on lähempänä CRLB:tä kuin IDFT-taajuusestimaatin MSE. Koska PCC saavuttaa tämän suorituskyvyn pienemmällä laskentakuormalla, se on soveliaampi kyseiseen sovellukseen. Lisäksi osoitetaan, että vaihe-estimaatin MSE pienenee, kun näytteenottotaajuutta tai mittausväliä kasvatetaan, tai kun salamoiden ja läheisellä taajuudella toimivien lähettimien aiheuttamat häiriöt poistetaan purskehäiriöiden poisto ja virheellisten ositteiden poisto -algoritmeilla. Lopuksi esitetään muutamia signaaliprosessoritoteutukseen (DSP) liittyviä yksityiskohtia, joilla voidaan pienentää laskentakuormaa.This thesis proposes a new method for estimating the unknown phase of a sampled sinusoid of known frequency. The method is called phase corrected correlation (PCC) and it is targeted specifically for the case, when there is a non-integer number of cycles in the measurement interval. Performance of the PCC phase estimate is studied by comparing its mean squared error (MSE) with the Cramér-Rao lower bound (CRLB). In order to simplify analysis and comparison with related methods, the selected signal model is a single sinusoid in additive white Gaussian noise. Two additional algorithms, burst noise removal and partition outlier removal, are proposed for decreasing the MSE of phase estimates in the presence of disturbances such as lightnings and interfering transmitters. PCC frequency estimate is obtained by observing signal phase change in consecutive measurement intervals. Frequency estimation performance and computational burden of the PCC is compared with Interpolated DFT (IDFT). The application domain is a meteorological sounding system for upper-air wind finding using Very Low Frequency (VLF) navigation systems. The problem is to estimate a minute frequency offset caused by the Doppler effect. Frequencies transmitted especially by the Russian Alpha radionavigation system are challenging: the estimation algorithm must be able handle a non-integer number of signal cycles in the 400 ms measurement interval. Most of the related frequency and phase estimation methods are not applicable to this estimation problem. Interpolated DFT (IDFT) may be feasible and therefore it is used as a benchmark. It is shown with computer simulations, that MSE of the phase estimate is close to the CRLB. The same applies to frequency estimates obtained by observing signal phase change in consecutive measurement intervals. Comparison with IDFT shows, that MSE of the PCC frequency estimate is closer to the CRLB as MSE of the IDFT frequency estimate. Moreover, PCC achieves this performance with lower computational burden, making it the preferred choice in this application. It is also shown that MSE of the phase estimate decreases as sampling rate or measurement interval is increased, and that MSE of the phase estimate decreases when interference is removed using burst noise removal and partition outlier removal algorithms. Finally, to achieve a computationally efficient digital signal processor (DSP) implementation, a number of implementation issues are covered