A new digital cochlea model neuro-spike representation of auditory signals and its application to classification of bat-like biosonar echoes

Title:

A new digital cochlea model neuro-spike representation of auditory signals and its application to classification of bat-like biosonar echoes

Creator:

Temel, Turgay

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:151f5bbb-6ea0-4995-bbf9-71d56f6c3d8f
uuid:151f5bbb-6ea0-4995-bbf9-71d56f6c3d8f

Subject:

Audio processing systems, pattern recognition and classification, cochlea model, and spike coding

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

For an improved neuro-spike representation of auditory signals within cochlea models, a new digital ARMA-type low-pass filter structure is proposed. It is compared to more conventional AR-type counterpart on a classification of biosonar echoes, in which echoes from various tree species insonified with a bat-like chirp call are converted to biologically plausible feature vectors. Next, parametric and non-parametric models of the class-conditional densities are built from the echo feature vectors. The models are deployed in single-shot and sequential-decision classification algorithms. The results indicate that the proposed ARMA filter structure offers an improved single-echo classification performance, which leads to faster sequential-decision making than its AR-type counterpart.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2010 Volume:20 | Number:2

Harvested from:

CDK

Metadata only:

false