geometric algebra applications vol de bayro corrochano eduardo (35 résultats)

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Hardcover. Etat : Near Fine - Fine condition. NOT a library discard (illustrateur). 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.

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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a unified mathematical treatment of diverse problems in thegeneral domain of robotics and associated fields using Clifford or geometric alge-bra. By addressing a wide spectrum of problems in a common language, it offersboth fresh insights and new solutions that are useful to scientists and engineersworking in areas related with robotics.It introduces non-specialists to Clifford and geometric algebra, and provides ex-amples to help readers learn how to compute using geometric entities and geomet-ric formulations. It also includes an in-depth study of applications of Lie grouptheory, Lie algebra, spinors and versors and the algebra of incidence using theuniversal geometric algebra generated by reciprocal null cones.Featuring a detailed study of kinematics, differential kinematics and dynamicsusing geometric algebra, the book also develops Euler Lagrangeand Hamiltoni-ans equations for dynamics using conformal geometric algebra, and the recursiveNewton-Euler using screw theory in the motor algebra framework. Further, itcomprehensively explores robot modeling and nonlinear controllers, and discussesseveral applications in computer vision, graphics, neurocomputing, quantum com-puting, robotics and control engineering using the geometric algebra framework.The book also includes over 200 exercises and tips for the development of futurecomputer software packages for extensive calculations in geometric algebra, and aentire section focusing on how to write the subroutines in C++, Matlab and Mapleto carry out efficient geometric computations in the geometric algebra framework.Lastly, it shows how program code can be optimized for real-time computations.An essential resource for applied physicists, computer scientists, AI researchers,roboticists and mechanical and electrical engineers, the book clarifies and demon-strates the importance of geometric computing for building autonomous systemsto advance cognitive systems research.

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Buch. Etat : 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.

Buch. Etat : Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 680 pp. Englisch.

Etat : As New. Unread book in perfect condition.

Etat : As New. Unread book in perfect condition.

Taschenbuch. Etat : 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.

Buch. Etat : 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.

Taschenbuch. Etat : Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 776 pp. Englisch.

Buch. Etat : Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 776 pp. Englisch.

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Hardcover. Etat : Brand New. 629 pages. 9.25x6.10x1.42 inches. In Stock.

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Paperback. Etat : New. New. book.

Hardcover. Etat : New. New. book.

Hardcover. Etat : Brand New. 778 pages. 9.25x6.10x1.80 inches. In Stock.

Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Offers in a compact and complete way the theory and methods to apply Geometric Algebra to Robotics Introduces the basics of geometric algebra to specialists and non- specialists in a gentle and comprehensive manner using examples and abundant figu.

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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents a unified mathematical treatment of diverse problems in thegeneral domain of robotics and associated fields using Clifford or geometric alge-bra. By addressing a wide spectrum of problems in a common language, it offersboth fresh insights and new solutions that are useful to scientists and engineersworking in areas related with robotics.It introduces non-specialists to Clifford and geometric algebra, and provides ex-amples to help readers learn how to compute using geometric entities and geomet-ric formulations. It also includes an in-depth study of applications of Lie grouptheory, Lie algebra, spinors and versors and the algebra of incidence using theuniversal geometric algebra generated by reciprocal null cones.Featuring a detailed study of kinematics, differential kinematics and dynamicsusing geometric algebra, the book also develops Euler Lagrange and Hamiltoni-ans equations for dynamics using conformal geometric algebra, and the recursiveNewton-Euler using screw theory in the motor algebra framework. Further, itcomprehensively explores robot modeling and nonlinear controllers, and discussesseveral applications in computer vision, graphics, neurocomputing, quantum com-puting, robotics and control engineering using the geometric algebra framework.The book also includes over 200 exercises and tips for the development of futurecomputer software packages for extensive calculations in geometric algebra, and aentire section focusing on how to write the subroutines in C++, Matlab and Mapleto carry out efficient geometric computations in the geometric algebra framework.Lastly, it shows how program code can be optimized for real-time computations.An essential resource for applied physicists, computer scientists, AI researchers,roboticists and mechanical and electrical engineers, the book clarifies and demon-strates the importance of geometric computing for building autonomous systemsto advance cognitive systems research. 632 pp. Englisch.

Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents a unified mathematical treatment of diverse problems in thegeneral domain of robotics and associated fields using Clifford or geometric algebra. By addressing a wide spectrum of problems in a common language, it offersboth fresh insights and new solutions that are useful to scientists and engineersworking in areas related with robotics.It introduces non-specialists to Clifford and geometric algebra, and provides examples to help readers learn how to compute using geometric entities and geometric formulations. It also includes an in-depth study of applications of Lie grouptheory, Lie algebra, spinors and versors and the algebra of incidence using theuniversal geometric algebra generated by reciprocal null cones.Featuring a detailed study of kinematics, differential kinematics and dynamicsusing geometric algebra, the book also develops Euler Lagrangeand Hamiltonians equations for dynamics using conformal geometric algebra, and the recursiveNewton-Euler using screw theory in the motor algebra framework. Further, itcomprehensively explores robot modeling and nonlinear controllers, and discussesseveral applications in computer vision, graphics, neurocomputing, quantum computing, robotics and control engineering using the geometric algebra framework.The book also includes over 200 exercises and tips for the development of futurecomputer software packages for extensive calculations in geometric algebra, and aentire section focusing on how to write the subroutines in C++, Matlab and Mapleto carry out efficient geometric computations in the geometric algebra framework.Lastly, it shows how program code can be optimized for real-time computations.An essential resource for applied physicists, computer scientists, AI researchersroboticists and mechanical and electrical engineers, the book clarifies and demonstrates the importance of geometric computing for building autonomous systemsto advance cognitive systems research.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 632 pp. Englisch.