loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Qianglong Zeng 1 and Ganwen Zeng 2

Affiliations: 1 Bellevue High School, United States ; 2 Data I/O Corporation, United States

ISBN: 978-972-8865-61-0

Keyword(s): Bayesian inference, neural network, Adaptive signal processing

Related Ontology Subjects/Areas/Topics: Adaptive Signal Processing and Control ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Neural Networks Based Control Systems ; Signal Processing, Sensors, Systems Modeling and Control

Abstract: The primary advantages of high performance associative memory model are its ability to learn fast, store correctly, retrieve information similar to the human “content addressable” memory and it can approximate a wide variety of non-linear functions. Based on a distributed associative neural network, a Bayesian inference probabilistic neural network is designed implementing the learning algorithm and the underlying basic mathematical idea for the adaptive noise cancellation. Simulation results using speech corrupted with low signal to noise ratio in telecommunication environment shows great signal enhancement. A system based on the described method can store words and phrases spoken by the user in a communication channel and subsequently recognize them when they are pronounced as connected words in a noisy environment. The method guarantees system robustness in respect to noise, regardless of its origin and level. New words, pronunciations, and languages can be introduced to the system in an incremental, adaptive mode. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 34.237.51.35

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Zeng Q.; Zeng G. and (2006). BAYESIAN INFERENCE IN A DISTRIBUTED ASSOCIATIVE NEURAL NETWORK FOR ADAPTIVE SIGNAL PROCESSING.In Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-972-8865-61-0, pages 177-181. DOI: 10.5220/0001202101770181

@conference{icinco06,
author={Qianglong Zeng and Ganwen Zeng},
title={BAYESIAN INFERENCE IN A DISTRIBUTED ASSOCIATIVE NEURAL NETWORK FOR ADAPTIVE SIGNAL PROCESSING},
booktitle={Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2006},
pages={177-181},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001202101770181},
isbn={978-972-8865-61-0},
}

TY - CONF

JO - Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - BAYESIAN INFERENCE IN A DISTRIBUTED ASSOCIATIVE NEURAL NETWORK FOR ADAPTIVE SIGNAL PROCESSING
SN - 978-972-8865-61-0
AU - Zeng, Q.
AU - Zeng, G.
PY - 2006
SP - 177
EP - 181
DO - 10.5220/0001202101770181

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.