Non-stationary effects are ubiquitous in real world data. In many settings, the observed signals are a mixture of underlying stationary and non-stationary sources that cannot be measured directly. For example, in EEG analysis, electrodes on the scalp record the activity from several sources located inside the brain, which one could only measure invasively. Discerning stationary and non-stationa...

In this paper, we propose a novel watermarking method that has robust and transparent properties by perceptually tuned characteristics and stationary Generalized Gaussian model based on Multiwavelet transform domain. The proposed method embeds watermark signals at the texture and edge regions using the perceptual stochastic model with content adaptivenes. This method adopts stationary Generaliz...

A novel enhancement system is developed that exploits the properties of stationary regions localized in both time and frequency. This system selects stationary time-frequency (TF) regions and adaptively enhances each region according to its local signal-tonoise ratio (LSNR) while utilizing both the acoustical knowledge of speech and the masking properties of the human auditory system. Each regi...

in recent years there has been considerable interest in the synthesis and separation of enantiomers of organic compounds especially because of their importance in the biochemistry and pharmaceutical industry. high-performance liquid chromatography is a very useful method for the direct separation of enantiomers. however, about 30−40 years ago, commercially available chiral stationary phases wer...

According to the short-time Fourier transform theory and principle of digital filtering, this paper established a mathematical model called collection of voice signal collection at different spectrum. The voice signal was a non-stationary process, while the standard Fourier transform only applied to the periodic signal, transient signals or stationary random signal. Therefore, the standard Four...

Signal fading refers to the rapid change in received signal strength over a small travel distance or time interval. This occurs because in a multipath propagation environment, the signal received by the mobile at any point in space may consist of a large number of plane waves having randomly distributed amplitudes, phases, delays and angles of arrival. These multipath components combine vectori...

Current multimedia technologies call for efficient ways of representing signals. We review several efficient methods for signal representation, emphasizing potential applications in signal compression and denoising. We pay special attention to the representations which are adapted to “non-stationary” features of signals, in particular the classes of bilinear representations, and their approxima...

A Gaussian channel, when corrupted by an additive Gaussian interfering signal whose complete sample sequence is known non-causally to the transmitter but not to the receiver, has the same capacity as if the interfering signal were not present. This is true even when the noise and interference are not necessarily stationary or ergodic.

Classification requires building invariant representations relatively to groups of deformations that preserve signal classes. Recursive interferometry computes invariants with a cascade of complex wavelet transforms and modulus operators. The resulting representation is stable relatively to elastic deformations and provides invariant representations of stationary processes. It maps signals to a...

Non-stationary prediction-error filters (PEF’s) provide an effective means for separating signal from coherent noise in electroseismic data. The electroseismic signal is much weaker than the noise, so we can not rely on windowing, transforms, or other alterations of the original data to create models for the PEF estimation. Instead, we design signal PEF’s using the physical predictability of th...