VLSI Design of a neurohardware processor implementing the Kohonen Neural Network algorithm
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Summary
The VLSI design and implementation of a neurohardware for high-speed pattern recognition is proposed, which implements the Kohonen Neural Network for pattern classification and the combined FPGA-VLSI approach was proposed.
- Type
- dissertation
- Published
- 2005-12-01
- Cited by
- 0
- References
- 35
- OpenAlex
- https://openalex.org/W65858876
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:108267670
Keywords
Field-programmable gate array, Very-large-scale integration, VHDL, Computer science, Artificial neural network
References
- Fundamentals of Digital Logic with VHDL Design with CD-ROM
- Neurocomputers: an overview of neural networks in VLSI
- Neural networks using bit stream arithmetic: a space efficient implementation
- SOM hardware with acceleration module for graphical representation of the learning process
- Neural Network Adaptations to Hardware Implementations
- Building neural networks
- Neural Computing - An Introduction
- Logic Synthesis Using Synopsys
- Artificial Neural Networks: Theory and Applications
- Fundamentals Of Neural Networks
- Hardware-friendly learning algorithms for neural networks: an overview
- Self-Organizing Maps
- Phonetic typewriter for Finnish and Japanese
- A low-cost neuroprocessor board for emulating the SOFM neural model
- THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS
- Computer Systems Organization and Architecture
- UCI Repository of machine learning databases
- The 'neural' phonetic typewriter
- Hardware synthesis for neural networks from a behavioral description with VHDL
- Logic synthesis speeds ASIC design
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