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The Certainty
The book deals with the Information theory and explores the logical methods in determination of a measure in the field probability associated with the information processing for real time systems and models, such as to distinguish the certainty that is a power function, and identify the uncertainty which as an unknown variable is a complement of the function, in order to achieve accuracy of the intended results to precisely meet with the predictions.
A General Theory of System Safety
There is the field of probability or chance, between 0 and 1, and other known measures associated with these, all of which cannot be seen but only known; and there is the larger field, which apart from the now redefined sub-field of probability, comes fully in to light; whereby, a unique relationship amongst the opposite sense existing between logical frameworks and those between mathematical operations, begin to reciprocate equally with reason and thus forming a general theory of system safety.
Principles of Probability Relations and Philosophical Science Part-I
The elements of a risk matrix [K] that is determinable from the elements of the state transition matrix [M] for the different states of a known system at each instant of time, expressed in an exponential form gives the instantaneous system reliability matrix [R], by the process of matrix inversion. Similarly, the complements of matrix elements are found by the identity matrix that has unit elements. The rules of algebra are applicable, as is the scalar multiplication and addition and so for the
Quantum Of Time: Transformations
: The book provides comprehensive details on the state transition for a system by transformations, using the Golden ratio, as invariable over finite distances in the quantum of time.
The Random Ordering
That there is the random variable having a frequency in a given sample space is not an unknown variable as there is the reliability for a well defined system with an assumption of complete independence; and a model needs to be built for the known system and the system surrounding the system, based on the power functions of the certainty and its complement the uncertainty for the elements as the measures of possibility, where an inverse gives rise to the function of entropy or disorder which is increasing as ever; and the random phenomena are determinable is the assertion.
The Theory of Certainty
"On one end there is the well known probability theory viewed with the systemic approach now meets the best of adaptations for the known system, as for instance the compatibility of work and flow by two engines pulling a train over a specified distance; and on the other end we have the new theory of certainty which enable us with the most aesthetic choice in hand among all the symmetry to rely on, as for instance the assurance of new stipulated intervals or time of operation; where both infallibly lead to great gains in a real time scenario."
Artificial Neural Networks and Machine Learning – ICANN 2023
The 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023. The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications.
The Special Theory
The book is an extension of an earlier published book by the same author and by same publisher, titled "The Theory of Certainty"
How to Think About Algorithms
This textbook, for second- or third-year students of computer science, presents insights, notations, and analogies to help them describe and think about algorithms like an expert, without grinding through lots of formal proof. Solutions to many problems are provided to let students check their progress, while class-tested PowerPoint slides are on the web for anyone running the course. By looking at both the big picture and easy step-by-step methods for developing algorithms, the author guides students around the common pitfalls. He stresses paradigms such as loop invariants and recursion to unify a huge range of algorithms into a few meta-algorithms. The book fosters a deeper understanding of how and why each algorithm works. These insights are presented in a careful and clear way, helping students to think abstractly and preparing them for creating their own innovative ways to solve problems.
