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{
"item_title" : "Knowledge-Based Neurocomputing",
"item_author" : [" Eyal Kolman", "Michael Margaliot "],
"item_description" : "In this monograph, the authors introduce a novel fuzzy rule-base, referred to as the Fuzzy All-permutations Rule-Base (FARB). They show that inferring the FARB, using standard tools from fuzzy logic theory, yields an input-output map that is mathematically equivalent to that of an artificial neural network. Conversely, every standard artificial neural network has an equivalent FARB. The FARB-ANN equivalence integrates the merits of symbolic fuzzy rule-bases and sub-symbolic artificial neural networks, and yields a new approach for knowledge-based neurocomputing in artificial neural networks.",
"item_img_path" : "https://covers3.booksamillion.com/covers/bam/3/64/209/985/3642099858_b.jpg",
"price_data" : {
"retail_price" : "109.99", "online_price" : "109.99", "our_price" : "109.99", "club_price" : "109.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : ""
}
}
Overview
In this monograph, the authors introduce a novel fuzzy rule-base, referred to as the Fuzzy All-permutations Rule-Base (FARB). They show that inferring the FARB, using standard tools from fuzzy logic theory, yields an input-output map that is mathematically equivalent to that of an artificial neural network. Conversely, every standard artificial neural network has an equivalent FARB.
The FARB-ANN equivalence integrates the merits of symbolic fuzzy rule-bases and sub-symbolic artificial neural networks, and yields a new approach for knowledge-based neurocomputing in artificial neural networks.
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Details
- ISBN-13: 9783642099854
- ISBN-10: 3642099858
- Publisher: Springer
- Publish Date: October 2010
- Dimensions: 9.21 x 6.14 x 0.25 inches
- Shipping Weight: 0.39 pounds
- Page Count: 100
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