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Thomas Martinetz (born 2 January 1962 in Nettesheim) is a German physicist and neuro-informatician.
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Thomas Martinetz (born 2 January 1962 in Nettesheim) is a German physicist and neuro-informatician.
Thomas Martinetz studied mathematics and physics at the Technical University of Munich, where he earned his doctorate in theoretical biophysics under Klaus Schulten in 1992 after several years as a guest at the University of Illinois at Urbana-Champaign. [1] After working in the central research and development department of Siemens AG, in 1996 he moved to a professorship at the Institute for Neuroinformatics of the Ruhr University Bochum and took over the management of the Center for Neuroinformatics GmbH. In 1999 he accepted a call to the University of Lübeck as director of the Institute for Neuro- and Bioinformatics. From 2006 to 2008 he was Vice-Rector of the University of Lübeck, and from 2008 to 2011 Vice-President for Research and Technology Transfer. Since 2013 he is chairman of the Senate of the University of Lübeck.
His major contribution in the field of neuroinformatics is the so-called Neural gas, a variant of self-organizing maps.
He is co-founder of the software companies Consideo, the Pattern Recognition Company and gestigon.
The Center for Neuroinformatics GmbH, whose management he took over in 1996, was awarded in the same year with the Innovation Award of the German economy. awarded him as a "courageous entrepreneur", and in 2011 he received the transfer award of the Innovation Foundation Schleswig-Holstein.
Artificial neural networks are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains.
NeuroEvolution of Augmenting Topologies (NEAT) is a genetic algorithm (GA) for the generation of evolving artificial neural networks developed by Kenneth Stanley and Risto Miikkulainen in 2002 while at The University of Texas at Austin. It alters both the weighting parameters and structures of networks, attempting to find a balance between the fitness of evolved solutions and their diversity. It is based on applying three key techniques: tracking genes with history markers to allow crossover among topologies, applying speciation to preserve innovations, and developing topologies incrementally from simple initial structures ("complexifying").
Teuvo Kalevi Kohonen was a Finnish computer scientist. He was professor emeritus of the Academy of Finland.
Neural gas is an artificial neural network, inspired by the self-organizing map and introduced in 1991 by Thomas Martinetz and Klaus Schulten. The neural gas is a simple algorithm for finding optimal data representations based on feature vectors. The algorithm was coined "neural gas" because of the dynamics of the feature vectors during the adaptation process, which distribute themselves like a gas within the data space. It is applied where data compression or vector quantization is an issue, for example speech recognition, image processing or pattern recognition. As a robustly converging alternative to the k-means clustering it is also used for cluster analysis.
Neuroinformatics is the field that combines informatics and neuroscience. Neuroinformatics is related with neuroscience data and information processing by artificial neural networks. There are three main directions where neuroinformatics has to be applied:
Eduardo Daniel Sontag is an Argentine-American mathematician, and distinguished university professor at Northeastern University, who works in the fields control theory, dynamical systems, systems molecular biology, cancer and immunology, theoretical computer science, neural networks, and computational biology.
Jacek M. Zurada serves as a Professor of Electrical and Computer Engineering Department at the University of Louisville, Kentucky. His M.S. and Ph.D degrees are from Politechnika Gdaṅska ranked as #1 among Polish universities of technology. He has held visiting appointments at Swiss Federal Institute of Technology, Zurich, Princeton, Northeastern, Auburn, and at overseas universities in Australia, Chile, China, France, Germany, Hong Kong, Italy, Japan, Poland, Singapore, Spain, and South Africa. He is a Life Fellow of IEEE and a Fellow of International Neural Networks Society and Doctor Honoris Causa of Czestochowa Institute of Technology, Poland.
Sami Erol Gelenbe, a Turkish and French computer scientist, electronic engineer and applied mathematician, pioneered the field of Computer System and Network Performance in Europe. Active in European Union research projects, he is Professor in the Institute of Theoretical and Applied Informatics of the Polish Academy of Sciences (2017-), Associate Researcher in the I3S Laboratory and Abraham de Moivre Laboratory. Previous Chaired professorships include the University of Liège (1974-1979), University Paris-Saclay (1979-1986), University Paris Descartes (1986-2005), ECE Chair at Duke University (1993-1998), University Chair Professor and Director of EECS, University of Central Florida (1998-2003), and Dennis Gabor Professor and Head of Intelligent Systems and Networks, Imperial College (2003-2019).
Spiking neural networks (SNNs) are artificial neural networks that more closely mimic natural neural networks. In addition to neuronal and synaptic state, SNNs incorporate the concept of time into their operating model. The idea is that neurons in the SNN do not transmit information at each propagation cycle, but rather transmit information only when a membrane potential—an intrinsic quality of the neuron related to its membrane electrical charge—reaches a specific value, called the threshold. When the membrane potential reaches the threshold, the neuron fires, and generates a signal that travels to other neurons which, in turn, increase or decrease their potentials in response to this signal. A neuron model that fires at the moment of threshold crossing is also called a spiking neuron model.
In the mathematical theory of artificial neural networks, universal approximation theorems are results that put limits on what neural networks can theoretically learn, i.e. that establish the density of an algorithmically generated class of functions within a given function space of interest. Typically, these results concern the approximation capabilities of the feedforward architecture on the space of continuous functions between two Euclidean spaces, and the approximation is with respect to the compact convergence topology. What must be stressed, is that while some functions can be arbitrarily well approximated in a region, the proofs do not apply outside of the region, i.e. the approximated functions do not extrapolate outside of the region. That applies for all non-periodic activation functions, i.e. what's in practice used and most proofs assume.
Gail Alexandra Carpenter is an American cognitive scientist, neuroscientist and mathematician. She is now a "Professor Emerita of Mathematics and Statistics, Boston University." She had also been a Professor of Cognitive and Neural Systems at Boston University, and the director of the Department of Cognitive and Neural Systems (CNS) Technology Lab at Boston University.
Dimitri Panteli Bertsekas is an applied mathematician, electrical engineer, and computer scientist, a McAfee Professor at the Department of Electrical Engineering and Computer Science in School of Engineering at the Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, and also a Fulton Professor of Computational Decision Making at Arizona State University, Tempe.
Informatics is the study of computational systems. According to the ACM Europe Council and Informatics Europe, informatics is synonymous with computer science and computing as a profession, in which the central notion is transformation of information. In other countries, the term "informatics" is used with a different meaning in the context of library science, in which case it is synonymous with data storage and retrieval.
Halbert Lynn White Jr. was the Chancellor’s Associates Distinguished Professor of Economics at the University of California, San Diego, and a Fellow of the Econometric Society and the American Academy of Arts and Sciences.
Robert Kozma is First Tennessee University Professor of Mathematics at the University of Memphis.
In computer science, an evolving intelligent system is a fuzzy logic system which improves the own performance by evolving rules. The technique is known from machine learning, in which external patterns are learned by an algorithm. Fuzzy logic based machine learning works with neuro-fuzzy systems.
An adaptive neuro-fuzzy inference system or adaptive network-based fuzzy inference system (ANFIS) is a kind of artificial neural network that is based on Takagi–Sugeno fuzzy inference system. The technique was developed in the early 1990s. Since it integrates both neural networks and fuzzy logic principles, it has potential to capture the benefits of both in a single framework.
Pedro Antonio Valdes-Sosa is a Cuban neuroscientist who currently serves as the General Vice-Director for Research of the Cuban Neurosciences Center, which he cofounded in 1990. Valdes-Sosa is also member of the editorial boards of journals Neuroimage, Medicc, Audiology and Neurotology, PLosOne and Frontiers, Neuroimage and Brain Connectivity. His work includes statistical analysis of electrophysiological measurements, neuroimaging, nonlinear dynamical modeling of brain functions and Software and electrophysiological equipment development.
Klaus Schulten was a German-American computational biophysicist and the Swanlund Professor of Physics at the University of Illinois at Urbana-Champaign. Schulten used supercomputing techniques to apply theoretical physics to the fields of biomedicine and bioengineering and dynamically model living systems. His mathematical, theoretical, and technological innovations led to key discoveries about the motion of biological cells, sensory processes in vision, animal navigation, light energy harvesting in photosynthesis, and learning in neural networks.
Klaus-Robert Müller is a German computer scientist and physicist, most noted for his work in machine learning and brain–computer interfaces.
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