Online web session (second half of video, after 32 minutes of intro)
ABSTRACT
In this video conference, two new algorithms for learning Feed-Forward Artificial Neural Network are presented. In the introduction, a brief description of the development of the existing algorithms and their flaws are shown. The second part describes the first new algorithm - Bipropagation. The basic idea is given first, followed by a detailed description of the algorithm. In the third part yet another new algorithm is given, called Border Pairs Method. Again is first given a basic idea and then follows a detailed description of the algorithm. In the fourth part, the results and findings of experimental work are presented. In the conclusion, it is found that two described algorithms are fast and reliable - the second one is also constructive.SPEAKER
Bojan PLOJ, PhD
Born 1965 in Maribor, Slovenia, Europe
Thesis Border Pairs Method for learning of neural network
Job 1 year R&D engineer at Birostroj Computers
10 years teaching at Electronics high school in Ptuj
4 years assistant professor University of Maribor
7 years lecturer at Higher vocational college Ptuj
3 years lecturer at the college of Ptuj (Artificial intelligence)
Research
Voice recognition with NN
Hexapod gait control with NN
Bipropagation algorithm for learning NN
Border pairs method for learning NN
Artificial intelligence (AI) is a relatively young branch of science that stirs the imagination of many. Even movie directors from hollywood are not exceptions. Development in AI area is very fast and there is no indication that this will change soon. I still remember my first contact with learning devices. This happend at the end of the last millennium when I realized neural networks (NN). They have immediately attracted my attention, because such devices were not known till then. NN are made along the lines of mammalian brain. During the learning NN extract the essence from the data. After the learning we can ask NN questions. It gives us the right answers even to questions that during learning did not participate. NN learns autonomously and therefore may exceed the teacher's (poeple's) knowledge. Here are some important achievements of artificial intelligence: A couple of years ago the co...
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