A Novel Weighted LBG Algorithm for Neural Spike Compression

Abstract— In this paper, we present a weighted Linde-BuzoGray algorithm (WLBG) as a powerful and efficient technique for compressing neural spike data. We compare this technique with the recently proposed Self-Organizing Map with Dynamic Learning (SOM-DL) and the traditional SOM. A significant achievement of WLBG over SOM-DL is a 15dB increase in the SNR of the spike data apart from having a compression ratio

• Type: Conference
• Year: 2007
• Where: IJCNN
• Authors: Sudhir Rao, António R. C. Paiva, Jose C. Principe
• Keywords: IJCNN 2007, Neural Spike Data, Spike Data, Weighted Linde-buzogray Algorithm