Of Interaural Time Difference by Spiking Neural Networks Zihan Pan, Malu Zhang, Jibin Wu, and Haizhou Li, Fellow, IEEE
JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 1 Multi-Tones’ Phase Coding (MTPC) of Interaural Time Difference by Spiking Neural Networks Zihan Pan, Malu Zhang, Jibin Wu, and Haizhou Li, Fellow, IEEE Abstract—Inspired by the mammal’s auditory localization (in humans 20Hz to 2kHz) for MSO and high frequencies (in pathway, in this paper we propose a pure spiking neural humans >2kHz) for LSO [7]. From the information flow point network (SNN) based computational model for precised sound of view, the location-dependent information from the sounds, localization in the noisy real-world environment, and implement this algorithm in a real-time robotic system with microphone or aforementioned time or intensity differences, are encoded array. The key of this model relies on the MTPC scheme, which into spiking pulses in the MSO and LSO. After that, they are encodes the interaural time difference (ITD) cues into spike projected to the inferior colliculus (IC) in the mid-brain, where patterns. This scheme naturally follows the functional structures the IC integrates both cues for estimating the sound source of human auditory localization system, rather than artificially direction [8]. The most successful model for ITD encoding computing of time difference of arrival. Besides, it highlights the advantages of SNN, such as event-driven and power efficiency. in MSO and cortex decoding might be the “place theory” by The MTPC is pipeliend with two different SNN architectures, an American psychologist named Lloyd Jeffress [9], which is the convolutional SNN and recurrent SNN, by which it shows the also referred to as Jeffress model hereafter.
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