Neural Signal Processing using Discrete Wavelet Transform for Neural Interfaces

J. Lee, D. Kipke
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引用次数: 5

Abstract

This paper presents a neural signal processing ASIC based on discrete wavelet transform (DWT). The recorded neural signals from 256 channels are analyzed by fast DWT algorithm with special ALUs, then, compressed by run-length encoders (RLE). The processed data are delivered through RF links and reconstructed in a host receiver. This design operates at 200 MHz clock with 2.5 V and was implemented with TSMC 0.25 mum technology. Recorded neural data test shows 1:89:3 (1.12%) compression rate and perfect in-band noise rejection
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基于离散小波变换的神经接口信号处理
提出了一种基于离散小波变换的神经信号处理专用集成电路。采用快速小波变换算法对256个信道的神经信号进行分析,然后用RLE进行压缩。处理后的数据通过射频链路传送,并在主机接收器中重构。本设计工作于200 MHz时钟,电压为2.5 V,采用台积电0.25 μ m技术实现。记录的神经数据测试显示1:89:3(1.12%)的压缩率和良好的带内噪声抑制
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