In this paper, we study the performance limits of recovering the support of a sparse signal based on quantized noisy random projections. Although the problem of support recovery of sparse signals with real valued noisy projections with different types of projection matrices has been addressed by several authors in the recent literature, very few attempts have been made for the same problem with quantized compressive measurements. In this paper, we derive performance limits of support recovery of sparse signals when the quantized noisy corrupted compressive measurements are sent to the decoder over additive white Gaussian noise channels. The sufficient conditions which ensure the perfect recovery of sparsity pattern of a sparse signal from coarsely quantized noisy random projections are derived when the maximum-likelihood decoder is used. More specifically, we find the relationships among the parameters, namely the signal dimension $N$, the sparsity index $K$, the number of noisy projections $M$, the number of quantization levels $L$, and measurement signal-to-noise ratio which ensure the asymptotic reliable recovery of the support of sparse signals when the entries of the measurement matrix are drawn from a Gaussian ensemble.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Comparing Different Resampling Methods in Predicting Students Performance Using Machine Learning Techniques ABSTRACT: Predicting students' performance is one of the most valuable and important research areas in
PROJECT TITLE : Using Cost-Sensitive Learning and Feature Selection Algorithms to Improve the Performance of Imbalanced Classification ABSTRACT: The problem of unbalanced data is common in network intrusion detection, spam filtering,
PROJECT TITLE : Deep Neural Networks Improve Radiologists Performance in Breast Cancer Screening ABSTRACT: To classify mammograms for breast cancer screening, we developed a deep convolutional neural network that was trained and
PROJECT TITLE : Predicting Detection Performance on Security X-Ray Images as a Function of Image Quality ABSTRACT: Research into how image quality impacts work performance is a hot topic in many industries. The security X-ray
PROJECT TITLE : A Novel Control Scheme for Enhancing the Transient Performance of an Islanded Hybrid AC-DC Microgrid ABSTRACT: In this research, we present an innovative supplementary feature for increasing the transient performance

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry