On some common compressive sensing recovery algorithms and applications-Review paper
Compressive Sensing, as an emerging technique in signal processing is reviewed in this
paper together with its common applications. As an alternative to the traditional signal …
paper together with its common applications. As an alternative to the traditional signal …
Sparse linear prediction and its applications to speech processing
The aim of this paper is to provide an overview of Sparse Linear Prediction, a set of speech
processing tools created by introducing sparsity constraints into the linear prediction …
processing tools created by introducing sparsity constraints into the linear prediction …
A new way to enhance speech signal based on compressed sensing
We propose a novel speech enhancement approach based on compressed sensing. The
method performs noise subtraction in the measurement domain in addition to sparse …
method performs noise subtraction in the measurement domain in addition to sparse …
[كتاب][B] Digital Signal Processing with Matlab Examples, Volume 3
JM Giron-Sierra - 2017 - Springer
Probably the most important technological invention of the previous century was the
transistor. And another very important invention was the digital computer, which got a …
transistor. And another very important invention was the digital computer, which got a …
Retrieving sparse patterns using a compressed sensing framework: applications to speech coding based on sparse linear prediction
Encouraged by the promising application of compressed sensing in signal compression, we
investigate its formulation and application in the context of speech coding based on sparse …
investigate its formulation and application in the context of speech coding based on sparse …
Analysis of the reconstruction of sparse signals in the DCT domain applied to audio signals
Sparse signals can be reconstructed from a reduced set of signal samples using
compressive sensing (CS) methods. The discrete cosine transform (DCT) can provide highly …
compressive sensing (CS) methods. The discrete cosine transform (DCT) can provide highly …
Adaptive measurement matrix design in direction of arrival estimation
Advances in compressed sensing (CS) theory have brought new perspectives to encoding
and decoding of signals with sparse representations. The encoding strategies are …
and decoding of signals with sparse representations. The encoding strategies are …
A survey on recent advances in speech compressive sensing
Compressive sensing (CS) is one of the upcoming fields which have paved its way for
different approaches towards the signal acquisition and processing systems. In past years …
different approaches towards the signal acquisition and processing systems. In past years …
Compressive sensing: Methods, techniques, and applications
According to the latest research, it is very much clear that in future we require a huge amount
of data as modern advancement in communication and signal processing generates a large …
of data as modern advancement in communication and signal processing generates a large …
Compressive speech enhancement
This paper presents an alternative approach to speech enhancement by using compressed
sensing (CS). CS is a new sampling theory, which states that sparse signals can be …
sensing (CS). CS is a new sampling theory, which states that sparse signals can be …