MLP Design Method Optimized for Hidden Neurons on FPGA


The KIPS Transactions:PartB , Vol. 13, No. 4, pp. 429-438, Aug. 2006
10.3745/KIPSTB.2006.13.4.429,   PDF Download:

Abstract

Neural Networks(NNs) are applied for solving a wide variety of nonlinear problems in several areas, such as image processing, pattern recognition etc. Although NN can be simulated by using software, many potential NN applications required real-time processing. Thus they need to be implemented as hardware. The hardware implementation of multi-layer perceptrons(MLPs) in several kind of NNs usually uses a fixed-point arithmetic due to a simple logic operation and a shorter processing time compared to the floating-point arithmetic. However, the fixed-point arithmetic-based MLP has a drawback which is not able to apply the MLP software that use floating-point arithmetic. We propose a design method for MLPs which has the floating-point arithmetic-based fully-pipelining architecture. It has a processing speed that is proportional to the number of the hidden nodes. The number of input and output nodes of MLPs are generally constrained by given problems, but the number of hidden nodes can be optimized by user experiences. Thus our design method is using optimized number of hidden nodes in order to improve the processing speed, especially in field of a repeated processing such as image processing, pattern recognition, etc.


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from September 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article
[IEEE Style]
D. W. Kyoung and K. C. Jung, "MLP Design Method Optimized for Hidden Neurons on FPGA," The KIPS Transactions:PartB , vol. 13, no. 4, pp. 429-438, 2006. DOI: 10.3745/KIPSTB.2006.13.4.429.

[ACM Style]
Dong Wuk Kyoung and Kee Chul Jung. 2006. MLP Design Method Optimized for Hidden Neurons on FPGA. The KIPS Transactions:PartB , 13, 4, (2006), 429-438. DOI: 10.3745/KIPSTB.2006.13.4.429.