FPGA implementation of a spike-based sound localization system

被引：0

作者：

Ponca, M ^{[1
]}

Schauer, C ^{[1
]}

机构：

[1] Tech Univ Ilmenau, Dept Elect, D-98684 Ilmenau, Germany

来源：

ARTIFICIAL NEURAL NETS AND GENETIC ALGORITHMS | 2001年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we describe an implementation of a part of binaural sound localization system, which uses Interaural Time Differences (ITDs). All neurons are simulated by a spike response model, which includes postsynaptic potentials (PSPs) and refractory period. A winner-take-all (WTA) network selects the dominant source from the representation of the sound's angles of incidence. At the beginning, we explain the principles of the localization system, and then details of implementation of its input part: Inner Hair Cells (IHCs), responsible for transforming input sound signals into spikes.

引用

下载

页码：212 / 215

页数：4

共 50 条

[21] Design of a spike-based architecture for Energy Harvested RFID-System
Machnoor, Manjunath
Gaggatur, Javed S.
Sanjeev, K.
2015 IEEE BOMBAY SECTION SYMPOSIUM (IBSS), 2015,
[22] Spike-Timing-Based Computation in Sound Localization
Goodman, Dan F. M.
Brette, Romain
PLOS COMPUTATIONAL BIOLOGY, 2010, 6 (11)
[23] Spike-based reinforcement learning of navigation
Eleni Vasilaki
Robert Urbanczik
Walter Senn
Wulfram Gerstner
BMC Neuroscience, 9 (Suppl 1)
[24] Biologically plausible VLSI neural network implementation with asynchronous neuron and spike-based synapse
Han, IS
Proceedings of the International Joint Conference on Neural Networks (IJCNN), Vols 1-5, 2005, : 3244 - 3248
[25] Low-Voltage Implementation of Neuromorphic Circuits for a Spike-Based Learning Control Module
Akbari, Meysam
Tang, Kea-Tiong
IEEE ACCESS, 2022, 10 : 2619 - 2630
[26] Spikemax: Spike-based Loss Methods for Classification
Shrestha, Sumit Bam
Zhu, Longwei
Sun, Pengfei
2022 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2022,
[27] Implementation of an FPGA-Based Vision Localization
Lee, Wen-Yo
Bo-Jhih, Chen
Wu, Chieh-Tsai
Shih, Ching-Long
Tsai, Ya-Hui
Fan, Yi-Chih
Lee, Chiou-Yng
Chen, Ti-Hung
GENETIC AND EVOLUTIONARY COMPUTING, VOL II, 2016, 388 : 233 - 242
[28] Spike-Based Population Coding and Working Memory
Boerlin, Martin
Deneve, Sophie
PLOS COMPUTATIONAL BIOLOGY, 2011, 7 (02)
[29] A Spike-Based Model of Neuronal Intrinsic Plasticity
Li, Chunguang
Li, Yuke
IEEE TRANSACTIONS ON AUTONOMOUS MENTAL DEVELOPMENT, 2013, 5 (01) : 62 - 73
[30] Spike-based Learning Rules for Face Recognition
Du, Chunlin
Nan, Ying
Yan, Rui
2017 6TH DATA DRIVEN CONTROL AND LEARNING SYSTEMS (DDCLS), 2017, : 536 - 541

← 1 2 3 4 5 →