DocumentCode :
395282
Title :
A high-performance multi-purpose DSP architecture for signal processing research
Author :
Morrison, Scott A. ; Parks, Jeremy S. ; Gugel, Karl S.
Author_Institution :
Appl. Digital Design Lab., Florida Univ., Gainesville, FL, USA
Volume :
2
fYear :
2003
fDate :
6-10 April 2003
Abstract :
This paper presents a powerful and flexible digital signal processing (DSP) architecture based on the Texas Instruments TMS320VC33 DSP and high speed PCI bus. The DSP board provides a convenient, flexible means to test signal processing algorithms in real-time hardware. Algorithms implemented for several research projects include normalized least mean square (NLMS) adaptive filter, recurrent neural network (RNN), Viterbi decoding, and adaptive beamforming. The low-cost, reconfigurable system is presently being used in various research projects such as multiple channel sampling and filtering MEMS-based acoustic arrays, wireless LAN hardware implementation, and neural net classification of primate EEG waveforms. The paper provides a detailed description of the DSP board, the theory behind its selection of components, and how it is being used in the earlier mentioned research projects.
Keywords :
Viterbi decoding; acoustic arrays; adaptive filters; array signal processing; digital signal processing chips; electroencephalography; least mean squares methods; micromechanical devices; real-time systems; reconfigurable architectures; recurrent neural nets; signal sampling; system buses; wireless LAN; MEMS-based acoustic arrays; NLMS; RNN; Texas Instruments TMS320VC33; Viterbi decoding; adaptive beamforming; adaptive filter; digital signal processing; high speed PCI bus; high-performance architecture; multi-purpose DSP architecture; multiple channel sampling; neural net classification; normalized least mean square; primate EEG waveforms; real-time hardware; reconfigurable system; recurrent neural network; wireless LAN hardware implementation; Acoustic testing; Adaptive filters; Decoding; Digital signal processing; Hardware; Instruments; Recurrent neural networks; Signal processing; Signal processing algorithms; Viterbi algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
ISSN :
1520-6149
Print_ISBN :
0-7803-7663-3
Type :
conf
DOI :
10.1109/ICASSP.2003.1202438
Filename :
1202438
Link To Document :
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