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Chapter 10:
Processes of Perception and Analysis
Section 1:
Introduction
There are no notes for this section.
Section 2:
What Perception and Analysis Do
There are no notes for this section.
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
Practicalities [of data compression]
History [of data compression]
Number representations
Lengths of [number] representations
Completeness [of number representations]
[Number representations in] practical computing
Run-length encoding
Huffman coding
Maximal block compression
Arithmetic coding
Pointer-based encoding
LZW algorithms
Recursive subdivision [encoding]
2D run-length encoding
Section 6:
Irreversible Data Compression
History [of irreversible data compression]
Orthogonal bases
Walsh transforms
Walsh spectra
Hadamard matrices
Image averaging
Practical image compression
Fourier transforms
JPEG compression
Wavelets
Sound compression
Section 7:
Visual Perception
Color vision
Nerve cells
The visual system
Feedback [in visual processing]
Scale invariance [in vision]
History [of vision research]
Implementation [of texture perception model]
Testing the [texture perception] model
Related [texture perception] models
Image processing
Real textures
Statistical methods [for texture analysis]
Camouflage
Halftoning
Generating textures
Moire patterns
Perception and presentation
Section 8:
Auditory Perception
Sounds
Auditory system
Chords
History [of auditory perception]
Sonification
Implementation [of sound]
[Sounds based on] time variation
[Sounds based on] musical scores
Recognizing repetition [in sounds]
Sound compression
Spectra [of sequences]
Spectra of substitution systems
[Sequences with] flat spectra
Nested vibrations
[Spectra of] random block sequences
Spectra of cellular automata
2D spectra
Diffraction patterns
Section 9:
Statistical Analysis
History [of statistics]
Practical statistics
Time series
Origin of probabilities
Probabilistic models
Binomial distribution
Estimation of parameters [in probabilistic models]
Complexity of models
Markov processes
[Models involving] non-local processes
Block frequencies [in sequences]
LFSR sequences
Entropy estimates [for sequences]
Tests of randomness
Difference tables
Randomized algorithms
Section 10:
Cryptography and Cryptanalysis
History [of cryptography]
Basic theory [of cryptography]
[Redundancy in] text
Cryptanalysis
Linear feedback shift registers
LFSR cryptanalysis
Rule 30 cryptography
[Cryptographic] properties of rule 30
Directional sampling [in cellular automata]
Alternative rules [for cryptography]
Nonlinear feedback shift registers
Backtracking [in cellular automata]
Deducing cellular automaton rules
[Cryptanalysis of] linear congruential generators
Digit sequence encryption
Problem-based cryptography
Factoring integers
RSA cryptography
Quadratic residue sequences
Section 11:
Traditional Mathematics and Mathematical Formulas
Practical empirical mathematics
Difference tables and polynomials
Implementation [of repetitive array]
Nested patterns and numbers
Implementation [of finite automata for nested patterns]
[Patterns from] arbitrary digit operations
Generating functions [for nested patterns]
Pascal's triangle
Nesting in bitwise functions
Trinomial coefficients
Gegenbauer functions
Standard mathematical functions
[Generating functions for] 1D sequences
Multidimensional additive rules
Continuous generalizations [of additive rules]
Nested continuous functions
GCD array
Power cellular automata
Computing powers [of numbers]
Complex powers [of numbers]
[Algebraic computation of] additive cellular automata
The more general case [of computation speed ups]
Evaluation chains
Boolean formulas
DNF minimization
[Boolean] formula sizes
Cellular automaton [Boolean] formulas
Primitive [Boolean] functions
Multilevel [Boolean] formulas
Nand expressions
Cellular automaton [Nand] formulas
Binary decision diagrams
History [of Boolean functions]
Reversible logic
[Reduced formulas in] continuous systems
Section 12:
Human Thinking
The brain
History [of ideas about thinking]
The future [of machine thinking]
Sleep
Pointer encoding [and memory]
Hashing
[Identifying] similar words
[Memory analogs with] numerical data
Error-correcting codes
Matrix memories
Neural network models
[Human] memory
[Cognitive] child development
Computer interfaces
Context-free languages
[Computer and human] languages
Computer language fluency
Brainteasers
Human generation of randomness
Game theory
Games between programs
Section 13:
Higher Forms of Perception and Analysis
Biological [forms of] perception
Evolving to predict [data]
Familiar features [of perceived data]
Relativism and postmodernism