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—Sparse signal recovery finds use in a variety of practical applications, such as signal and image restoration and the recovery of signals acquired by compressive sensing. In this paper, we present two generic VLSI architectures that implement the approximate message passing (AMP) algorithm for sparse signal recovery. The first architecture, referred to as(More)
—One of the key tasks in cognitive radio and communications intelligence is to detect active bands in the radio-frequency (RF) spectrum. In order to perform spectral activity detection in wideband RF signals, expensive and energy-inefficient high-rate analog-to-digital converters (ADCs) in combination with sophisticated digital detection circuitry are(More)
We demonstrate real-time audio signal restoration using techniques from compressive sensing (CS) and sparse signal recovery. In particular, we show an FPGA prototype implementation of the approximate message passing (AMP) algorithm, which removes clicks and pops from corrupted audio signals.
—Spectral activity detection in wideband radio-frequency (RF) signals for cognitive-radio applications typically necessitates expensive and energy-inefficient analog-to-digital converters (ADCs). In this paper, we present a novel compressive sensing (CS)-based analog front-end, which is able to sample sparse wideband RF signals at low cost and low power.(More)
Spectral activity detection of wideband radio-frequency (RF) signals for cognitive radios typically requires expensive and energy-inefficient analog-to-digital converters (ADCs). Fortunately, the RF spectrum is-in many practical situations-sparsely populated, which enables the design of so called analog-to-information (A2I) converters. A2I converters are(More)
—We demonstrate the restoration of audio signals corrupted by clicks and pops using techniques from sparse signal recovery and compressive sensing. The demonstration features real-time signal restoration using the approximate message passing algorithm on an FPGA prototyping board. To highlight the restoration performance of our implementation, we remove(More)
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