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To realize Electrocardiography (ECG) signals monitoring systems, compressive sensing (CS) is a new technique to reduce power of biosensors and data transmission. Instead of spending high complexity on reconstructing back to data domain to do signal analysis, compressed analysis (CA) exploits the data structure preserved by CS to directly analyze in the compressed domain. However, compressively-sensed...
Wireless sensor networks (WSNs) show immense promise in many applications, such as environmental monitoring and remotely metering. Compressive sensing (CS) is a novel signal processing that has been envisioned as a useful regime to address the energy and scaling constraints in WSNs. CS is able to move the burden of sensory nodes to central cloud/server. However, prevailing CS reconstruction algorithms...
Technology scaling enables Chip Multiprocessors (CMPs) a promising approach to powerful performance within a chip. However, increasing transistor density makes them more susceptible to transient faults. Even worse, process variation due to unstable manufacturing makes the reliability problem more complicated. In recent years, there is a trend towards exploiting the inherent core redundancy characteristic...
To fit into multiple communication standards, flexible Low-Density Parity-Check (LDPC) decoding is desirable to be implemented in a chip multiprocessor (CMP) system. However, reliability issues, such as soft errors and timing errors, are severer in future advanced CMP systems when CMOS technology scale. Therefore, enhancing error resilience for a CMP system becomes an important design issue. In this...
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