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| Preface | ||
| 1 | Is Entscheidungsproblem Solvable? Beyond Undecidability of Turing Machines and Its Consequence for Computer Science and Mathematics | 1 |
| 2 | Specification Language Design for Hybrid Systems | 33 |
| 3 | Modelling, Analysis, Monitoring and Control of the Internet to Provide Quality of Service | 53 |
| 4 | Function of Factor Dynamics: Time Evolution of the Latent Structure | 94 |
| 5 | Error and Computational Complexity in Engineering | 110 |
| 6 | Entropy and Counting | 146 |
| 7 | Models of Distributed Systems: Graphical Representations for Mobile Environments | 169 |
| 8 | Cryptographic Applications | 214 |
| 9 | Pattern Recognition (PR) and Machine Learning (ML): Current Trends and Some Applications | 230 |
| 10 | Fuzzy Regression Analysis via Neuro-Fuzzy Network and Its Application to System Modelling and Optimization | 306 |
| 11 | Sparse Rule-Based Fuzzy Reasoning | 345 |
| 12 | Efficient Rare Event Simulation Using Importance Sampling: An Introduction | 357 |
| 13 | Agent Searching | 397 |
| 14 | Competitive Deadline Scheduling via Extra Resources | 445 |
| 15 | Fast Algorithms and Scientific Computation | 467 |
| 16 | Online Optimization Through Mining the Offline Optimum | 505 |
| Price | Condition | Delivery | Seller | Action |
| $148.00 | Digital |
| WonderClub |
R T
reviewed Computational Mathematics, Modelling and Algorithms on November 03, 2016
Computational Mathematics
I normally don't do this, but I'm going to copy/paste this review across three separate books: Chaitin's "The Unknowable", "The Limits of Mathematics", and "Exploring Randomness".
All three are all thin, overpriced, but very approachable books on Algorithmic Information Theory. Themes include:
- Undecidability, as the basis of formulating a new kind of randomness measure for numbers that have already been generated (not just restricting randomness measures to the processes that generate numbers).
- Chaitin's Omega constant, which is the probability that universal Turning machine will halt on random input. This constant is "maximally unknowable", but that doesn't stop one from performing math with it.
- Philosophy surrounding these topics.
One might underestimate Kolmogorov's contributions, given how ridiculously self-promoting Chaitin has been with this AIT. However, the topics are interesting enough that he's easy to forgive. And he uses many code demonstrations (LISP) to make concrete examples out of the math.
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