a collection of M-files to study concepts in the following areas of Fuzzy-Set-Theory: Fuzzy or Multivalued Logic, The Calculus of Fuzzy, Quantities, Approximate Reasoning, Possibility Theory, Fuzzy Control, Neuro-Fuzzy Systems.
FISMAT accommodates different arithmetic operators, fuzzification and defuzzification algorithm, implication relations, and different method of approximate Reasoning such as Compositional Rule of Inference (CRI) and Approximate Analogical Reasoning Scheme based on Similarity Measure.
Semantic analysis of multimedia content is an on going research
area that has gained a lot of attention over the last few years.
Additionally, machine learning techniques are widely used for multimedia
analysis with great success. This work presents a combined approach
to semantic adaptation of neural network classifiers in multimedia framework.
It is based on a fuzzy Reasoning engine which is able to evaluate
the outputs and the confidence levels of the neural network classifier, using
a knowledge base. Improved image segmentation results are obtained,
which are used for adaptation of the network classifier, further increasing
its ability to provide accurate classification of the specific content.
People have vast background knowledge to cope with everyday situations.
We don t have to be told everything explicitly because we can call on the background knowledge.
We use `default knowledge to handle situations where knowledge is incomplete.
This is called common sense Reasoning.
Artificial Intelligence (AI) is a big field, and this is a big book. We have tried to explore the
full breadth of the field, which encompasses logic, probability, and continuous mathematics;
perception, Reasoning, learning, and action; and everything from microelectronic devices to
robotic planetary explorers. The book is also big because we go into some depth.
The subtitle of this book is “A Modern Approach.” The intended meaning of this rather
empty phrase is that we have tried to synthesize what is now known into a common frame-
work, rather than trying to explain each subfield of AI in its own historical context. We
apologize to those whose subfields are, as a result, less recognizable.
ets gre 數學考試講義，
Mathematical Conventions for the Quantutative Reasoning Measure of the GRE revised General Test
for the Quantitative Reasoning Measure of the GRE? revised General Test
