A Low-Power Area-Efficient Design and Comparative Analysis for High-Resolution Neural Data Compression

被引：0
|
作者：
Ashraf, Mohammed [1 ]
Mostafa, Hassan [1 ,2 ]
El-Adawy, Ahmed A. [1 ]
机构：
[1] Cairo Univ, Elect & Commun Engn Dept, Giza 12613, Egypt
[2] AUC & Zewail City Sci & Technol, Ctr Nanoelect & Devices, New Cairo 11835, Egypt
来源：
2016 28TH INTERNATIONAL CONFERENCE ON MICROELECTRONICS (ICM 2016) | 2016年
基金：
加拿大自然科学与工程研究理事会;
关键词：
Neural Signals; Multichannel Neural Recording; Data Compression; Image processing; Low-power Design; HW Implementation;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Nowadays, brain scientific research progress depends on signal compression at high spatial resolutions, for efficient storage and low-rate transmission through wireless connection to outside world. So that neural data compression at the implant site is necessary in order to conform with the wireless rates restrictions. In this paper, the high spatial correlation is utilized to increase the data compression ratio. Then we investigate and compare three different proposed low-power image compression algorithms based on discrete cosine transform (DCT) and discrete wavelet transform (DWT) to provide the best trade-off between hardware complexity and compression performance. Hence, we conclude that Adaptive 2D-DWT algorithm is a promising solution for low-power implantable devices.
引用
收藏
页码：217 / 220
页数：4
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