| _version_ |
1860799669300363264
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| building |
INTELEK Repository
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| collection |
Online Access
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| collectionurl |
https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072
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| date |
2017-02-15 14:22:18
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| eventvenue |
Phuket Thailand
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| format |
Restricted Document
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| id |
6926
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| institution |
UniSZA
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| originalfilename |
1682-01-FH03-FRIT-17-08229.jpg
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| person |
norman
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| recordtype |
oai_dc
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| resourceurl |
https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6926
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| spelling |
6926 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6926 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Conference Conference Paper image/jpeg inches 96 96 norman 1439 25 25 757 1439x757 2017-02-15 14:22:18 1682-01-FH03-FRIT-17-08229.jpg UniSZA Private Access Calculation of hybrid multi-layered perceptron neural network output using matrix multiplication After some studies on the HMLP neural network output equation, it was found out that parts of the equation resemble matrix multiplication operation. Therefore, an approach to calculate the output equation of the HMLP using matrix multiplication method was proposed. The proposed approach was simulated and compared with another approach to calculate HMLP output using loops. The result proved that the output of the HMLP calculated using matrix multiplication method is the same as when being calculated using looping method. When comparing the processing time of both methods, the matrix multiplication method is faster than looping method for HMLP with more nodes. However, looping method calculated the output faster for HMLP with less nodes. This paper presents part of an ongoing study with the goal to develop an architecture for implementing the HMLP on FPGA 3rd International Conference on Electronic Design, ICED 2016 Phuket Thailand
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| spellingShingle |
Calculation of hybrid multi-layered perceptron neural network output using matrix multiplication
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| summary |
After some studies on the HMLP neural network output equation, it was found out that parts of the equation resemble matrix multiplication operation. Therefore, an approach to calculate the output equation of the HMLP using matrix multiplication method was proposed. The proposed approach was simulated and compared with another approach to calculate HMLP output using loops. The result proved that the output of the HMLP calculated using matrix multiplication method is the same as when being calculated using looping method. When comparing the processing time of both methods, the matrix multiplication method is faster than looping method for HMLP with more nodes. However, looping method calculated the output faster for HMLP with less nodes. This paper presents part of an ongoing study with the goal to develop an architecture for implementing the HMLP on FPGA
|
| title |
Calculation of hybrid multi-layered perceptron neural network output using matrix multiplication
|
| title_full |
Calculation of hybrid multi-layered perceptron neural network output using matrix multiplication
|
| title_fullStr |
Calculation of hybrid multi-layered perceptron neural network output using matrix multiplication
|
| title_full_unstemmed |
Calculation of hybrid multi-layered perceptron neural network output using matrix multiplication
|
| title_short |
Calculation of hybrid multi-layered perceptron neural network output using matrix multiplication
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| title_sort |
calculation of hybrid multi-layered perceptron neural network output using matrix multiplication
|