| 000 | 03447cam a2200529Ki 4500 | ||
|---|---|---|---|
| 001 | 9781003154242 | ||
| 003 | FlBoTFG | ||
| 005 | 20240213122832.0 | ||
| 006 | m o d | ||
| 007 | cr cnu---unuuu | ||
| 008 | 210816s2021 flua ob 001 0 eng d | ||
| 040 |
_aOCoLC-P _beng _erda _epn _cOCoLC-P |
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| 020 |
_a9781000412567 _q(electronic bk.) |
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| 020 |
_a1000412563 _q(electronic bk.) |
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| 020 |
_a9781003154242 _q(electronic bk.) |
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| 020 |
_a1003154247 _q(electronic bk.) |
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| 020 |
_a9781000412604 _q(electronic bk. : EPUB) |
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| 020 |
_a1000412601 _q(electronic bk. : EPUB) |
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| 020 | _z9780367720292 | ||
| 020 | _z0367720299 | ||
| 035 | _a(OCoLC)1264086115 | ||
| 035 | _a(OCoLC-P)1264086115 | ||
| 050 | 4 |
_aQA76.9.L38 _bR58 2021 |
|
| 072 | 7 |
_aMAT _x002010 _2bisacsh |
|
| 072 | 7 |
_aMAT _x002000 _2bisacsh |
|
| 072 | 7 |
_aCOM _x014000 _2bisacsh |
|
| 072 | 7 |
_aPBF _2bicssc |
|
| 082 | 0 | 4 |
_a004.015113 _223 |
| 100 | 1 |
_aRitter, G. X., _eauthor. |
|
| 245 | 1 | 0 |
_aIntroduction to lattice algebra : _bwith applications in AI, pattern recognition, image analysis, and biomimetic neural networks / _cGerhard X. Ritter, Gonzalo Urcid. |
| 264 | 1 |
_aBoca Raton : _bChapman & Hall/CRC, _c2021. |
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| 300 |
_a1 online resource : _billustrations |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 520 | _aLattice 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 articial intelligence and computer science in general. Introduction to LatticeAlgebra: 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 articial intelligence with a focus on pattern recognition, multispectral image analysis, and biomimetic articial neural networks. The book is self-contained and - depending on the student's major - can be usedfor a senior undergraduate level or rst-year graduate level course. The book is also an ideal self-study guide for researchers and professionals in the above-mentioned disciplines. Features Filled with instructive examples and exercises to help build understanding Suitable for researchers, professionals and students, both in mathematics and computer science Every chapter consists of exercises with solution provided online at www.Routledge.com/9780367720292 | ||
| 588 | _aOCLC-licensed vendor bibliographic record. | ||
| 650 | 0 | _aLattice theory. | |
| 650 | 0 |
_aComputer science _xMathematics. |
|
| 650 | 0 |
_aArtificial intelligence _xMathematical models. |
|
| 650 | 7 |
_aMATHEMATICS / Algebra / Abstract _2bisacsh |
|
| 650 | 7 |
_aMATHEMATICS / Algebra / General _2bisacsh |
|
| 650 | 7 |
_aCOMPUTERS / Computer Science _2bisacsh |
|
| 700 | 1 |
_aUrcid, Gonzalo, _eauthor. |
|
| 856 | 4 | 0 |
_3Taylor & Francis _uhttps://www.taylorfrancis.com/books/9781003154242 |
| 856 | 4 | 2 |
_3OCLC metadata license agreement _uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf |
| 999 |
_c5915 _d5915 |
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