基于DHNN的纠单错码译码方法的研究

Investigation on Decoding of SEC Codes Using DHNN

利用神经网络动态系统中吸引子和吸引域的特性，本文提出了一类新型非线性纠单错码。这种码的原理简单，易于并行实现，因而具有较高的译码速度。

Based on the properties of attractors and their attraction basins, a new class of nonlinear single error correction (SEC) codes is proposed in this paper. Since this code has simple structure and is easy to be implemented in parallel, a rather high decoding speed might thus be expected.