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Convolutional Neural Network (CNN) is the state-of-the-art deep learning approach employed in various applications due to its remarkable performance. Convolutions in CNNs generally dominate the overall computation complexity and thus consume major computational power in real implementations. In this paper, efficient hardware architectures incorporating parallel fast finite impulse response (FIR) algorithm...
Long polar codes achieve the capacity of binary-input discrete memoryless channels when decoded with a successive cancelation (SC) algorithm. For polar codes with short or moderate length, the decoding performance of the SC algorithm is inferior, and the cyclic redundancy check (CRC) aided successive cancelation list (SCL) algorithm achieves significantly improved performance. In this paper, we propose...
Low-density parity-check (LDPC) codes are one of the most promising error-correcting codes approaching Shannon capacity and have been adopted in many applications. However, the efficient implementation of high-throughput LDPC decoders adaptable for various channel conditions still remains challenging. In this paper, a low-complexity reconfigurable VLSI architecture for high-speed LDPC decoders is...
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