## Mathematical Analysis of Evolution, Information, and Complexity (Google eBook)Mathematical Analysis of Evolution, Information, and Complexity deals with the analysis of evolution, information and complexity. The time evolution of systems or processes is a central question in science, this text covers a broad range of problems including diffusion processes, neuronal networks, quantum theory and cosmology. Bringing together a wide collection of research in mathematics, information theory, physics and other scientific and technical areas, this new title offers elementary and thus easily accessible introductions to the various fields of research addressed in the book. |

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### Contents

1 Weyls Law | 1 |

2 Solutions of Systems of Linear Ordinary Differential Equations | 73 |

3 A ScalarTensor Theory of Gravity with a Higgs Potential | 99 |

4 Relating Simulation and Modeling of Neural Networks | 137 |

5 Boolean Networks for Modeling Gene Regulation | 157 |

6 Symmetries in Quantum Graphs | 181 |

7 Distributed Architecture for SpeechControlled Systems Based on Associative Memories | 197 |

8 Machine Learning for Categorization of Speech Utterances | 219 |

11 Boosting Ensembles of Weak Classifiers in High Dimensional Input Spaces | 311 |

12 The Sampling Theorem in Theory and Practice | 333 |

13 Coding and Decoding of AlgebraicGeometric Codes | 355 |

14 Investigation of InputOutput Gain in Dynamical Systems for Neural Information Processing | 379 |

15 Wave Packet Dynamics and Factorization | 395 |

16 Isomorphism and Factorization Classical and Quantum Algorithms | 433 |

17 QuickSort from an Information Theoretic View | 455 |

465 | |

9 SemiSupervised Clustering in Functional Genomics | 243 |

10 Image Processing and Feature Extraction from a Perspective of Computer Vision and Physical Cosmology | 273 |

### Common terms and phrases

89069 Ulm Germany AdaBoost algorithm analysis applied associative memories asymptotic behavior biclusters Boolean networks classical clustering complex compute constant convergence coprime corresponding cosmological decoding defined denotes density derived Dirichlet Dirichlet Laplacian distribution domain dynamics eigenvalues error example factor feature extraction ﬁeld Figure filter Fourier transform function Gabor filter Gaussian gene given gravitational Higgs hypothesis input integral interaction isomorphism Laplacian linear mapping Math mathematical matrix methods modular exponentiation multiplication neural networks neurons nodes ofthe operator output parameters particles period physics Planck polynomial power series prime numbers problem processing quantum graphs quantum mechanics random sampling theorem scalar field Schrödinger equation Section sequence signal solution space spectral speech recognition structure subword units symmetry term tion trace formula University of Ulm utterance values vector Weyl Weyl’s law word zero