Notes

Chapter 10: Processes of Perception and Analysis


Section 1: Introduction


Section 2: What Perception and Analysis Do


Section 3: Defining the Notion of Randomness

Algorithmic information theory History [of randomness definitions] Inevitable regularities and Ramsey theory

Section 4: Defining Complexity

History [of complexity definitions]

Section 5: Data Compression

2D run-length encoding Arithmetic coding Completeness [of number representations] History [of data compression] Huffman coding Lengths of [number] representations LZW algorithms Maximal block compression Number representations [Number representations in] practical computing Pointer-based encoding Practicalities [of data compression] Recursive subdivision [encoding] Run-length encoding

Section 6: Irreversible Data Compression

Fourier transforms Hadamard matrices History [of irreversible data compression] Image averaging JPEG compression Orthogonal bases Practical image compression Sound compression Walsh spectra Walsh transforms Wavelets

Section 7: Visual Perception

Camouflage Color vision Feedback [in visual processing] Generating textures Halftoning History [of vision research] Image processing Implementation [of texture perception model] Moire patterns Nerve cells Perception and presentation Real textures Related [texture perception] models Scale invariance [in vision] Statistical methods [for texture analysis] Testing the [texture perception] model The visual system

Section 8: Auditory Perception

2D spectra Auditory system Chords Diffraction patterns History [of auditory perception] Implementation [of sound] Nested vibrations Recognizing repetition [in sounds] [Sequences with] flat spectra Sonification Sound compression Sounds [Sounds based on] musical scores [Sounds based on] time variation Spectra of cellular automata [Spectra of] random block sequences Spectra [of sequences] Spectra of substitution systems

Section 9: Statistical Analysis

Binomial distribution Block frequencies [in sequences] Complexity of models Difference tables Entropy estimates [for sequences] Estimation of parameters [in probabilistic models] History [of statistics] LFSR sequences Markov processes [Models involving] non-local processes Origin of probabilities Practical statistics Probabilistic models Randomized algorithms Tests of randomness Time series

Section 10: Cryptography and Cryptanalysis

Alternative rules [for cryptography] Backtracking [in cellular automata] Basic theory [of cryptography] Cryptanalysis [Cryptanalysis of] linear congruential generators [Cryptographic] properties of rule 30 Deducing cellular automaton rules Digit sequence encryption Directional sampling [in cellular automata] Factoring integers History [of cryptography] LFSR cryptanalysis Linear feedback shift registers Nonlinear feedback shift registers Problem-based cryptography Quadratic residue sequences [Redundancy in] text RSA cryptography Rule 30 cryptography

Section 11: Traditional Mathematics and Mathematical Formulas

[Algebraic computation of] additive cellular automata Binary decision diagrams [Boolean] formula sizes Boolean formulas Cellular automaton [Boolean] formulas Cellular automaton [Nand] formulas Complex powers [of numbers] Computing powers [of numbers] Continuous generalizations [of additive rules] Difference tables and polynomials DNF minimization Evaluation chains GCD array Gegenbauer functions [Generating functions for] 1D sequences Generating functions [for nested patterns] History [of Boolean functions] Implementation [of finite automata for nested patterns] Implementation [of repetitive array] Multidimensional additive rules Multilevel [Boolean] formulas Nand expressions Nested continuous functions Nested patterns and numbers Nesting in bitwise functions Pascal's triangle [Patterns from] arbitrary digit operations Power cellular automata Practical empirical mathematics Primitive [Boolean] functions [Reduced formulas in] continuous systems Reversible logic Standard mathematical functions The more general case [of computation speed ups] Trinomial coefficients

Section 12: Human Thinking

Brainteasers [Cognitive] child development [Computer and human] languages Computer interfaces Computer language fluency Context-free languages Error-correcting codes Game theory Games between programs Hashing History [of ideas about thinking] Human generation of randomness [Human] memory [Identifying] similar words Matrix memories [Memory analogs with] numerical data Neural network models Pointer encoding [and memory] Sleep The brain The future [of machine thinking] [Underlying] structure of Mathematica

Section 13: Higher Forms of Perception and Analysis

Biological [forms of] perception Evolving to predict [data] Familiar features [of perceived data] Relativism and postmodernism

From Stephen Wolfram: A New Kind of Science [citation]