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Sparsity In Machine Learning: An Information Selecting Perspective, Siwei Feng
Sparsity In Machine Learning: An Information Selecting Perspective, Siwei Feng
Doctoral Dissertations
Today we are living in a world awash with data. Large volumes of data are acquired, analyzed and applied to tasks through machine learning algorithms in nearly every area of science, business, and industry. For example, medical scientists analyze the gene expression data from a single specimen to learn the underlying causes of disease (e.g. cancer) and choose the best treatment; retailers can know more about customers' shopping habits from retail data to adjust their business strategies to better appeal to customers; suppliers can enhance supply chain success through supply chain systems built on knowledge sharing. However, it is also …
A Discrete-Time Technique For Linearity Enhancement Of Wideband Receivers, Mohammad Ghadiri Sadrabadi
A Discrete-Time Technique For Linearity Enhancement Of Wideband Receivers, Mohammad Ghadiri Sadrabadi
Doctoral Dissertations
A new signal processing technique is introduced to enhance the linearity performance of wideband radio frequency (RF) receivers. The proposed technique combines the advancements in mixer first architectures with a library of binary sequences as local oscillator signals to enable wide instantaneous bandwidth and high linearity for the RF receiver. To do so, N-bit pseudo-random-binary-sequences (PRBS) are used as local oscillator signals. The RF input signal is multiplied with the PRBS at the mixer and then averaged over the full sequence. This in effect reduces the amplitude of the signal and improves the overall linearity of the system. In order …
Sequence Design Via Semidefinite Programming Relaxation And Randomized Projection, Dian Mo
Sequence Design Via Semidefinite Programming Relaxation And Randomized Projection, Dian Mo
Doctoral Dissertations
Wideband is a booming technology in the field of wireless communications. The receivers in wideband communication systems are expected to cover a very wide spectrum and adaptively extract the parts of interest. The literature has focused on mixing the input spectrum to baseband using a pseudorandom sequence modulation and recovering the received signals from linearly independent measurements by parallel branches to mitigate the pressures from required extreme high sampling frequency. However, a pseudorandom sequence provides no rejection for the strong interferers received together with weak signals from distant sources. The interferers cause significant distortion due to the nonlinearity of the …