EXPLOITING CORRELATION IN NEURAL SIGNALS FOR DATA COMPRESSION

被引：0

作者：

Schmale, S. ^{[1
]}

Hoeffmann, J. ^{[1
]}

Knoop, B. ^{[1
]}

Kreiselmeyer, G. ^{[2
]}

Hamer, H. ^{[2
]}

Peters-Drolshagen, D. ^{[1
]}

Paul, S. ^{[1
]}

机构：

[1] Univ Bremen, Inst Electrodynam & Microelect ITEM Me, D-28359 Bremen, Germany

[2] Univ Hosp Erlangen, Epilepsy Ctr Erlangen EZE, Erlangen, Germany

来源：

2014 PROCEEDINGS OF THE 22ND EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO) | 2014年

关键词：

Neural Signals; Correlation; Data Compression; Compressed Sensing; Sparse Coding;

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：

Progress in invasive brain research relies on signal acquisition at high temporal- and spatial resolutions, resulting in a data deluge at the (wireless) interface to the external world. Hence, data compression at the implant site is necessary in order to comply with the neurophysiological restrictions, especially when it comes to recording and transmission of neural raw data. This work investigates spatial correlations of neural signals, leading to a significant increase in data compression with a suitable sparse signal representation before the wireless data transmission at the implant site. Subsequently, we used the correlation-aware two-dimensional DCT used in image processing, to exploit spatial correlation of the data set. In order to guarantee a certain sparsity in the signal representation, two paradigms of zero forcing are evaluated and applied: Significant coefficients-and block sparsity-zero forcing.

引用

页码：2080 / 2084

页数：5

共 50 条

[21] On exploiting interbeat correlation in compressive sensing-based ECG compression
Polania, Luisa F.
Carrillo, Rafael E.
Blanco-Velasco, Manuel
Barner, Kenneth E.
COMPRESSIVE SENSING, 2012, 8365
[22] Comparison of Different Compression Schemes for Neural Spike Signals
Bihr, Ulrich
Haas, Michael
Anders, Jens
Ortmanns, Maurits
BIOMEDICAL ENGINEERING-BIOMEDIZINISCHE TECHNIK, 2014, 59 : S130 - S130
[23] Hierarchical neural network based compression of ECG signals
Karlik, B
COMPUTATIONAL SCIENCE - ICCS 2003, PT I, PROCEEDINGS, 2003, 2657 : 371 - 377
[24] Data compression and feature extraction of ECG signals
Saxena, SC
Sharma, A
Chaudhary, SC
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 1997, 28 (05) : 483 - 498
[25] Exploiting the inter-correlation of structural vibration signals for data loss recovery: A distributed compressive sensing based approach
Amini, Fereidoun
Hedayati, Yousef
Zanddizari, Hadi
Mechanical Systems and Signal Processing, 2021, 152
[26] Exploiting Noise Correlation for Channel Decoding with Convolutional Neural Networks
Liang, Fei
Shen, Cong
Wu, Feng
2018 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2018,
[27] Exploiting Correlation in Stochastic Computing based Deep Neural Networks
Frasser, Christiam F.
Linares-Serrano, Pablo
Moran, Alejandro
Font-Rossello, Joan
Canals, V
Roca, Miquel
Serrano-Gotarredona, T.
Rossello, Josep L.
2021 XXXVI CONFERENCE ON DESIGN OF CIRCUITS AND INTEGRATED SYSTEMS (DCIS21), 2021, : 113 - 118
[28] Exploiting the inter-correlation of structural vibration signals for data loss recovery: A distributed compressive sensing based approach
Amini, Fereidoun
Hedayati, Yousef
Zanddizari, Hadi
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2021, 152
[29] Exploiting Data Compression for Adaptive Block Placement in Hybrid Caches
Kim, Beomjun
Kim, Yongtae
Nair, Prashant
Hong, Seokin
ELECTRONICS, 2022, 11 (02)
[30] Exploiting Data Compression to Mitigate Aging in GPU Register Files
Candel, Francisco
Valero, Alejandro
Petit, Salvador
Suarez-Gracia, Dario
Sahuquillo, Julio
2017 29TH INTERNATIONAL SYMPOSIUM ON COMPUTER ARCHITECTURE AND HIGH PERFORMANCE COMPUTING (SBAC-PAD), 2017, : 57 - 64

← 1 2 3 4 5 →