Computational Intelligence: Numerical intelligence. Three areas of science are summarized under the term CI, and are particularly suitable for dealing with very complex systems which are very difficult to analyze with classical methods. These areas are:

• Neural networks
• Evolutionary algorithms
• Fuzzy systems.

CI: see Computational Intelligence  

Fuzzy logic (FL): Processes not only 0 or 1, but all the in between values of 0 and 1 logically and correctly. Fuzzy systems can easily record expertise knowledge in a set of rules and play it back. See also: Link

Neural Networks (NN): Are information processing systems in biology, which consists of a large number of simple units (cells that make neurons), which is information sent to you in the form of activated cells via directed (links). Our brain and nervous system consists of neural networks. See also: http://en.wikipedia.org/wiki/Neural_network

Artificial Neural Networks (ANN): Are neural networks like natural networks which are made of simple functional units (neurons) and directed links with which are variable in importance. Can learn facts from training data e.g. mathematical context, graph curves or value relationships. See also: Link

Cognition (Latin cognoscere, "to know"):  is a behaviour controlled subsystem (for more advanced organisms, the brain) that transforms information. Cognition is a term used inconsistently, with reference to the information processing of people. Thinking in a broad sense is often meant by "cognitive". Although many people are conscious of cognitive processes, "cognition" and "awareness" have not got the same meaning. Thus, certain processes in humans can be unconscious and yet cognitive, an example of this is unconscious learning.

Cognitive processing systems: Systems that process information like that of a human being (see also cognition).

Evolutionary algorithms (EA): Algorithms that allow optimization like that of nature (Charles Darwin). Suitable for the optimization of solutions to daily problems in life. See also: Link

Genetic algorithms (GA): Genetic algorithms (GA) are algorithms that can handle none analytical solvable problems by repeatedly generating "solutions”. These solutions undergo change and combine with each other so they increasingly fit the given problem much better See also: Link

AFM: Atomic/Scanning Force Microscope (AFM or SFM as abbreviations, rare is RKM); is a specialized scanning probe microscope. It is an important tool in surface chemistry and is used for mechanical scanning of surfaces and the measurement of atomic forces in the nanometre scale.

Computer Vision: Can stand for machinery vision, the research area, the robot / computer vision teaching Link

CV: see Computer Vision

PTM: Photon Tunnelling Microscope

SONM:  Simultaneous Optical Near-field Microscope, this term has been introduced as a synonym for PTM, since this is in contrast to other well established near-field methods (AFM, NSOM) due to their simultaneous direct imaging techniques which are have not got a locking function.

TSD: Transducers

Training and further education

ECTS: credits for a Master's program in Europe for successful participants in the training and further education in CV & CI. Prerequisite are an academic qualification if the fields of computer science, engineering, mathematics, or industrial engineering in a European university and at least 2 years professional experience. The training course is there for recognized as a university course.

Applications

Data mining: search for knowledge in databases using conventional search methods and computational intelligence.

Controllers: Automated equipment, which permanently compares actual and given variables or command and control variables, with the aim of bringing them into line with ought having a difference occurring between them.
It is the basis of automation.

Knowledge Management: A technique to compress knowledge from existing ordered data sets, e.g. all documents of a company or all articles in an electronic journal.

• Computer Vision
• Computational intelligence (fuzzy systems, neural networks, evolutionary algorithms)