Introduction to lattice algebra : with applications n AI, pattern recognition, image analysis, and biomimetic neural networks / Gerhard X. Ritter and Gonzalo Urcid
Material type:
- 9780367722951
- 004.015113 RIT-G
Item type | Current library | Collection | Shelving location | Call number | Copy number | Status | Date due | Barcode | Item holds | |
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BITS Pilani Hyderabad | 003-007 | General Stack (For lending) | 004.15113 RIT-G (Browse shelf(Opens below)) | GBP 45.99 | Available | 49626 |
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004.1 TAN-S Quantum spin glasses, annealing and computation / | 004.1 WIC-A Principles of quantum artificial intelligence / | 004.1 YAN-N Quantum computing for computer scientists / | 004.15113 RIT-G Introduction to lattice algebra : with applications n AI, pattern recognition, image analysis, and biomimetic neural networks / | 004.16 BHU-K Advanced microprocessors and peripherals / | 004.16 BRE-B Intel microprocessors / | 004.16 BRE-B Intel microprocessors / |
Lattice theory extends into virtually every branch of mathematics, ranging from measure theory and convex geometry to probability theory and topology. A more recent development has been the rapid escalation of employing lattice theory for various applications outside the domain of pure mathematics. These applications range from electronic communication theory and gate array devices that implement Boolean logic to artificial intelligence and computer science in general. Introduction to Lattice Theory: With Applications in AI, Pattern Recognition, Image Analysis, and Biomimetic Neural Networks lays emphasis on two subjects, the first being lattice algebra and the second the practical applications of that algebra. This textbook is intended to be used for a special topics course in artificial intelligence with focus on pattern recognition, multispectral image analysis, and biomimetic artificial neural networks. The book is self-contained and - depending on the student's major - can be used at a senior undergraduate level or a first-year graduate level course. The book is also an ideal self-study guide for researchers and professionals in the above-mentioned disciplines
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