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Functional Inequalities Markov Semigroups and Spectral Theory
  • Language: en
  • Pages: 391

Functional Inequalities Markov Semigroups and Spectral Theory

  • Type: Book
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  • Published: 2006-04-06
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  • Publisher: Elsevier

In this book, the functional inequalities are introduced to describe:(i) the spectrum of the generator: the essential and discrete spectrums, high order eigenvalues, the principle eigenvalue, and the spectral gap;(ii) the semigroup properties: the uniform intergrability, the compactness, the convergence rate, and the existence of density;(iii) the reference measure and the intrinsic metric: the concentration, the isoperimetic inequality, and the transportation cost inequality.

Directory of Chinese Officials
  • Language: en
  • Pages: 180

Directory of Chinese Officials

  • Type: Book
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  • Published: 1985
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  • Publisher: Unknown

None

Measure-Valued Branching Markov Processes
  • Language: en
  • Pages: 481

Measure-Valued Branching Markov Processes

This book provides a compact introduction to the theory of measure-valued branching processes, immigration processes and Ornstein–Uhlenbeck type processes. Measure-valued branching processes arise as high density limits of branching particle systems. The first part of the book gives an analytic construction of a special class of such processes, the Dawson–Watanabe superprocesses, which includes the finite-dimensional continuous-state branching process as an example. Under natural assumptions, it is shown that the superprocesses have Borel right realizations. Transformations are then used to derive the existence and regularity of several different forms of the superprocesses. This techniq...

Introduction to Malliavin Calculus
  • Language: en
  • Pages: 182

Introduction to Malliavin Calculus

None

Dirichlet Forms and Stochastic Processes
  • Language: en
  • Pages: 457

Dirichlet Forms and Stochastic Processes

The series is aimed specifically at publishing peer reviewed reviews and contributions presented at workshops and conferences. Each volume is associated with a particular conference, symposium or workshop. These events cover various topics within pure and applied mathematics and provide up-to-date coverage of new developments, methods and applications.

Neural Information Processing. Models and Applications
  • Language: en
  • Pages: 763

Neural Information Processing. Models and Applications

  • Type: Book
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  • Published: 2010-11-18
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  • Publisher: Springer

The two volume set LNCS 6443 and LNCS 6444 constitutes the proceedings of the 17th International Conference on Neural Information Processing, ICONIP 2010, held in Sydney, Australia, in November 2010. The 146 regular session papers presented were carefully reviewed and selected from 470 submissions. The papers of part I are organized in topical sections on neurodynamics, computational neuroscience and cognitive science, data and text processing, adaptive algorithms, bio-inspired algorithms, and hierarchical methods. The second volume is structured in topical sections on brain computer interface, kernel methods, computational advance in bioinformatics, self-organizing maps and their applications, machine learning applications to image analysis, and applications.

Sensors, Measurement and Intelligent Materials
  • Language: en
  • Pages: 2969

Sensors, Measurement and Intelligent Materials

Selected papers from the 2012 International Conference on Sensors, Measurement and Intelligent Materials (ICSMIM 2012), December 26-27, 2012, Guilin, China

Neural Information Processing. Theory and Algorithms
  • Language: en
  • Pages: 740

Neural Information Processing. Theory and Algorithms

  • Type: Book
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  • Published: 2010-11-18
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  • Publisher: Springer

The two volume set LNCS 6443 and LNCS 6444 constitutes the proceedings of the 17th International Conference on Neural Information Processing, ICONIP 2010, held in Sydney, Australia, in November 2010. The 146 regular session papers presented were carefully reviewed and selected from 470 submissions. The papers of part I are organized in topical sections on neurodynamics, computational neuroscience and cognitive science, data and text processing, adaptive algorithms, bio-inspired algorithms, and hierarchical methods. The second volume is structured in topical sections on brain computer interface, kernel methods, computational advance in bioinformatics, self-organizing maps and their applications, machine learning applications to image analysis, and applications.

Malware Analysis Using Artificial Intelligence and Deep Learning
  • Language: en
  • Pages: 655

Malware Analysis Using Artificial Intelligence and Deep Learning

​This book is focused on the use of deep learning (DL) and artificial intelligence (AI) as tools to advance the fields of malware detection and analysis. The individual chapters of the book deal with a wide variety of state-of-the-art AI and DL techniques, which are applied to a number of challenging malware-related problems. DL and AI based approaches to malware detection and analysis are largely data driven and hence minimal expert domain knowledge of malware is needed. This book fills a gap between the emerging fields of DL/AI and malware analysis. It covers a broad range of modern and practical DL and AI techniques, including frameworks and development tools enabling the audience to innovate with cutting-edge research advancements in a multitude of malware (and closely related) use cases.

Neural Information Processing
  • Language: en
  • Pages: 799

Neural Information Processing

The three volume set LNCS 7062, LNCS 7063, and LNCS 7064 constitutes the proceedings of the 18th International Conference on Neural Information Processing, ICONIP 2011, held in Shanghai, China, in November 2011. The 262 regular session papers presented were carefully reviewed and selected from numerous submissions. The papers of part I are organized in topical sections on perception, emotion and development, bioinformatics, biologically inspired vision and recognition, bio-medical data analysis, brain signal processing, brain-computer interfaces, brain-like systems, brain-realistic models for learning, memory and embodied cognition, Clifford algebraic neural networks, combining multiple lear...