Bayro Corrochano Eduardo (155 results)

Hardcover. Condition: Very Good. 1st Edition. 235 pp. Tightly bound. Corners not bumped. Text is free of markings. No ownership markings. Published without a dust jacket. Printed boards. NOTE: The word "USED" is neatly stamped on the top fore-edge. First Edition / First Printing. 9,8,7,6,5,4,3,2,1.

Condition: New. pp. 256.

Condition: New.

Condition: very_good. Fast Shipping - Very good and clean conditions used book. Minor cosmetic defects may be present. Pages and cover intact. May include limited library marks, notes marks and highlighting.

Condition: New.

Condition: New.

Condition: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.

Hardcover. Condition: Near Fine - Fine condition. NOT a library discard (illustrator). First Edition. Springer, 2019. We have only this one copy, but it is available now and ready to ship today from Henderson, Nevada. The cover is in Near Fine condition but for a little bit of very minor shelfwear. NO chips, tears or fading. Square and tight. Corners are NOT bumped. NO owner's name or bookplate. NOTa library discard. NOT a remainder. FINE inside. Pages are crisp, clean and unmarked - apparently seldom if ever read. NO underlining. NO highlighting. NO margin notes. Bound in the original dark red pictorial laminated boards, lettered in bright white and yellow. From the publisher: "The goal of the Volume I Geometric Algebra for Computer Vision, Graphics and Neural Computing is to present a unified mathematical treatment of diverse problems in the general domain of artificial intelligence and associated fields using Clifford, or geometric, algebra. Geometric algebra provides a rich and general mathematical framework for Geometric Cybernetics in order to develop solutions, concepts and computer algorithms without losing geometric insight of the problem in question. Current mathematical subjects can be treated in an unified manner without abandoning the mathematical system of geometric algebra for instance: multilinear algebra, projective and affine geometry, calculus on manifolds, Riemann geometry, the representation of Lie algebras and Lie groups using bivector algebras and conformal geometry. By treating a wide spectrum of problems in a common language, this Volume I offers both new insights and new solutions that should be useful to scientists, and engineers working in different areas related with the development and building of intelligent machines. Each chapter is written in accessible terms accompanied by numerous examples, figures and a complementary appendix on Clifford algebras, all to clarify the theory and the crucial aspects of the application of geometric algebra to problems in graphics engineering, image processing, pattern recognition, computer vision, machine learning, neural computing and cognitive systems.". First Edition. Hardcover. Near Fine - Fine condition/No dust jacket, as issued. Illus. by NOT a library discard. 8vo. xxxiii, 742pp. Great Packaging, Fast Shipping.

Condition: New. pp. 550.

Condition: Usado - bueno.

Condition: Sehr gut. Zustand: Sehr gut | Seiten: 548 | Sprache: Englisch | Produktart: Bücher.

Condition: New.

Condition: New.

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The goal of Geometric Algebra Applications Vol. III: Integral Transforms, Machine Learning, and Quantum Computing is to present a unified mathematical treatment of diverse problems in the general domain like Clifford Fourier Transforms, Deep Learning and Geometric Algebra Convolutional Neural Networks, Quaternion Quantum Fourier Transform and Geometric Quantum Computing.Topics and features Introduces nonspecialists to Clifford, or geometric algebra and by example encourages the reader to learn to compute using geometric entities and geometric formulations. A study in depth for applications of Lie group theory, Lie algebra, projective geometry, and the algebra of incidence using the conformal geometric algebra. Features the computing frameworks of the linear model n-dimensional affine plane and the nonlinear model of Euclidean space known as the horosphere, and addresses the relationships of these models to conformal, affine, and projective geometries. Includes a thorough study of Integral transforms: Quaternion and Clifford Transforms, quaternion analytic signal, monogenic signals, Hilbert transform, Riesz transform, Clifford Fourier Transform, Quaternion Wavelet transforms, Quaternion Quantum Fourier Transform, 3D Radon Transform and Hough-Transform in geometric algebra. Color image processing using the color model HSV, Quaternion Split rotors and motors, and the space-time Lorentz transform. Geometric neural computing using Split Quaternions, Geometric Algebra neural networks, Clifford Support Vector Machine and Neuro Control. Thorough discussion of several tasks of computer vision, graphics, neurocomputing, and robotics. machine learning, Deep Learning and CNNs, and Geometric Quantum Computing using the geometric algebra framework. 130 exercises and hints for the development of future computer software packages for extensive calculations in geometric algebra. An entire section is dedicated to explaining how one should write the subroutines in C++, Phyton, Matlab, and Maple to carry out efficient geometric computations in the geometric algebra framework. Furthermore, it is shown how program code can be optimized for real-time computations.The book is an essential resource for applied mathematicians, physicists, computer scientists, graphics engineering, AI and Machine Learning researchers, roboticists and mechanical and electrical engineers, neurocomputing researchers, neuroscientists, and quantum computing specialists. It clarifies and demonstrates the importance of geometric computing for building autonomous systems and pushes forward advances in geometric cybernetics research.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The goal of the Volume I Geometric Algebra for Computer Vision, Graphics and Neural Computing is to present a unified mathematical treatment of diverse problems in the general domain of artificial intelligence and associated fields using Clifford, or geometric, algebra.Geometric algebra provides a rich and general mathematical framework for Geometric Cybernetics in order to develop solutions, concepts and computer algorithms without losing geometric insight of the problem in question. Current mathematical subjects can be treated in an unified manner without abandoning the mathematical system of geometric algebra for instance: multilinear algebra, projective and affine geometry, calculus on manifolds, Riemann geometry, the representation of Lie algebras and Lie groups using bivector algebras and conformal geometry. By treating a wide spectrum of problems in a common language, this Volume I offers both new insights and new solutions that should be useful to scientists, and engineers working in different areas related with the development and building of intelligent machines. Each chapter is written in accessible terms accompanied by numerous examples, figures and a complementary appendix on Clifford algebras, all to clarify the theory and the crucial aspects of the application of geometric algebra to problems in graphics engineering, image processing, pattern recognition, computer vision, machine learning, neural computing and cognitive systems.