Speech constitutes much of the communicated information; most other perceived audio signals do not carry nearly as much information. Indeed, much of the non-speech signals maybe classified as ‘noise’ in human communication. The process of separating conversational speech and noise is termed voice activity detection (VAD). This paper describes a new approach to VAD which is based on the Wavelet ...

During recent years, the silicon organic-inorganic compounds play the key role in medicinal chemistry and pharmaceutical industry. This is because of their similar chemical properties with carbon compounds. The second reason is related to their easy transfer from the cell membranes. So, molecular simulation and study the properties of novel organosilicon compounds can be more important. From th...

Noise reduction is a very meaningful but difficult task and it has been a subject of intense research in recent years. This paper introduces two popular noise reduction techniques and presents our simulation result of a noise reduction system. It is shown that the system reduces the noise almost completely while keeps the enhanced speech signal very similar to the original speech signal.

In the recent past, remotely sensed data with high spectral resolution has been made available and has been explored for various agricultural and geological applications. While these spectral signatures of the objects of interest provide important clues, the relatively poor spatial resolution of these hyperspectral images limits their utility and performance. In this context, hyperspectral imag...

Spectral element methods (SEM) are superior to general finite element methods (FEM) in achieving high order accuracy through p-type refinement. Owing to orthogonal polynomials in both expansion and test functions, the discretization errors in SEM could be reduced exponentially to machine zero so that the spectral convergence rate can be achieved. Inherited the advantage of FEM, SEM can enhance ...

We propose three new adaptive noise suppression algorithms for enhancing noise-corrupted speech: smoothed spectral subtraction (SSS), vector quantization of line spectral frequencies (VQ-LSF), and modiied Wiener ltering (MWF). SSS is an improved version of the well-known spectral subtraction algorithm, while the other two methods are based on generalized Wiener ltering. We have compared these t...

We explore the spectral dependence of fluorescence enhancement and the associated lifetime modification of fluorescent molecules coupled to single metal nanoparticles. Fluorescence lifetime imaging microscopy and single-particle dark-field spectroscopy are combined to correlate the dependence of fluorescence lifetime reduction on the spectral overlap between the fluorescence emission and the lo...

A new method is proposed for spectral quantitation of MRSI data. The method has two main features: 1) incorporation of prior spectral knowledge in the form of basis functions obtained by quantum simulation, and 2) incorporation of prior spatial knowledge by penalizing smoothness within each type of tissue. An efficient algorithm is also proposed to solve the underlying optimization problem, and...