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The Hardware Design and Implementation of a Signal Reconstruction Algorithm Based on Compressed Sensing

机译:基于压缩感知的信号重构算法的硬件设计与实现

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A fast and reliable signal reconstruction algorithm is the core part of the compressed sensing (CS) theory. As a reconstruction algorithm, interior point method has a high precision but it is time-consuming and needs large computation, so it is difficult to meet the actual needs. In view of the above problems, in this paper we propose a design for interior point method that is based on the Field Programmable Gate Array (FPGA )hardware platform, which is about the solution of linear equations that have the largest amount of computation. The array structure of the conjugate gradients (CG) coprocessor completes the main operations, and the parallel and pipeline coprocessor effectively take advantage of the inherent parallelism of the algorithm and the parallel structure of FPGA. Thus, it has greatly improved the processing speed.
机译:快速可靠的信号重建算法是压缩感知(CS)理论的核心部分。内点法作为一种重构算法,具有较高的精度,但费时,运算量大,难以满足实际需求。针对上述问题,本文提出了一种基于现场可编程门阵列(FPGA)硬件平台的内点法设计方法,该方法是关于计算量最大的线性方程组的求解。共轭梯度(CG)协处理器的阵列结构完成了主要操作,并行和流水线协处理器有效地利用了算法固有的并行性和FPGA的并行结构。因此,极大地提高了处理速度。

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