Sharif Digital Repository

Compressed Sensing (CS) technique refers to the digitalization process that efficiently reduces the number of measurements below the Nyquist rate while preserving signal structure. This technique was originally developed for the analysis of vector datasets. An x ∈R^n vector is transformed into an y ∈R^m vector so that n≪m. For a sufficient number of measurements, this transformation has been shown to preserve the signal structure. Therefore, the technique has been applied to machine learning applications.2D-CS was further developed for matrices (image datasets) so that they could be directly applied to matrices without flattening. X ∈R^(n×n) is transformed into Y ∈R^(m×m) via 2D-CD such... 

Analog-to-digital conversion and signal processing has been increasing due to its many advantages. So that mostly we prefer to convert signal from analog area to digital samples, then they are processed and finaly put the result signal at the system output. How ever because the restriction of the sampling rate, Prevent the spread of digital processing for the high-frequency signal (RF). In recent years, ADCs sampling rate rise up to several GHz (for example ADC with 4 GSPS and 12 bits for TI) that output of the these ADCs by powerful and fast FPGAs are processed but According to Shannon theorem band width of these ADCs is not desirable.the goal of this thesis uses of the compressed sensing... 

One of the funadmental problems in signal processing is finding the best sampling strategy of a continuous time signal, and then finding the best strategy for compressing the obtained signal samples. The sampling and compression steps are designed with the aim of minimizing the distortion of the reconstructed signal. The problem of finding the best sampling strategy has been widely studied in the signal processing literature. In particular, the Nyquist–Shannon sampling theorem gives a sufficient condition for perfect reconstruction of a continuous-time signal of finite bandwidth. Most of the signal processing literature deals with deterministic signals, with relatively less attention paid to... 

Passive wideband reconnaissance receivers, listen to the radio and radar signals in the environment and estimate their important parameters such as direction of arrival (DOA). The wideband attribute for these receivers is to refer to their ability to receive wideband signals.Due to the use of processing gain, LPI radars reduce their transmitted signal power to see and not to be seen. On the other hand reconnaissance receivers can not have much processing gain, because they do not know the nature of the transmitted signal; Therefore, to increase the operational range of these systems, it is necessary to increase the signal to noise power ratio (SNR). This thesis examines the use of antenna...