Conventional pulse-echo ultrasonic receivers rectify the received signal. Because the signature of the reflecting interfaces is modulated by the predominant ultrasonic frequency, interpretation of this signal in terms of the structure of the reflecting interfaces is difficult. Smoothing, as by an R-C filter, ameliorates this effect, giving a less confusing display at the expense of resolution. ...

Traditional feature extraction methods for automatic speech recognition (ASR), such as MFCC (Mel-frequency cepstral coefficients) and PLP (perceptual linear prediction) [6], are extracted from short-term spectral envelopes and can be used to realize promising ASR systems. On the other hand, features extracted by TRAPs-like classifiers [2] are based on long-term envelopes of narrow-band signals....

Hilbert transform (HT) is an important tool in constructing analytic signals for various purposes, such as envelope and instantaneous frequency analysis, amplitude modulation, shift invariant wavelet analysis and Hilbert-Huang decomposition. In this work we introduce a method for computation of HT based on the discrete cosine transform (DCT). We show that the Hilbert transformed signal can be o...

The paper considers the phase retrieval problem in N dimensional complex vector spaces. It provides two sets of deterministic measurement vectors which guarantee signal recovery for all signals, excluding only a specific subspace and a union of subspaces, respectively. A stable analytic reconstruction procedure of low complexity is given. Additionally it is proven that signal recovery from thes...

The analytic signal method via the Hilbert transform is a key tool in signal analysis and processing, especially in the time-frquency analysis. Imaging and other applications to multidimensional signals call for extension of the method to higher dimensions. We justify the usage of partial Hilbert transforms to define multidimensional analytic signals from both engineering and mathematical persp...

The paper considers the phase retrieval problem in N dimensional complex vector spaces. It provides two sets of deterministic measurement vectors which guarantee signal recovery for all signals, excluding only a specific subspace and a union of subspaces, respectively. A stable analytic reconstruction procedure of low complexity is given. Additionally it is proven that signal recovery from thes...

We have developed a novel approach to speech feature extraction based on a modulation model of a band-pass signal. Speech is processed by a bank of band-pass filters. At the output of the band-pass filters the signal is subjected to a log-derivative operation which naturally decomposes the band-pass signal into analytic (called ) and anti-analytic (called ) components. The average instantaneous...

The present thesis deals with two-dimensional signal processing for computer vision. The main topic is the development of a sophisticated generalization of the one-dimensional analytic signal to two dimensions. Motivated by the fundamental property of the latter, the invariance – equivariance constraint, and by its relation to complex analysis and potential theory, a two-dimensional approach is...