Logic Based Pattern Recognition - Ontology Content (2)

Logic based Pattern Recognition extends the well known similarity models, where the distance measure is the base instrument for recognition. Initial part (1) of current publication in iTECH-06 reduces the logic based recognition models to the reduced disjunctive normal forms of partially defined Boolean functions. This step appears as a way to alternative pattern recognition instruments through combining metric and logic hypotheses and features, leading to studies of logic forms, hypotheses, hierarchies of hypotheses and effective algorithmic solutions. Current part (2) provides probabilistic conclusions on effective recognition by logic means in a model environment of binary attributes.

Logic Based Pattern Recognition - Ontology Content (1)

* The research is supported partly by INTAS: 04-77-7173 project, http://www.intas.be

Exploration by Means of Computer Simulation of Nonlinear Hierarchical Structure of Neuronal Memory on the Model of Olfactory Bulb

Results of numerical experiments are introduced. Experiments were carried out by means of computer simulation on olfactory bulb for the purpose of checking of thinking mechanisms conceptual model, introduced in [2]. Key role of quasisymbol neurons in processes of pattern identification, existence of mental view, functions of cyclic connections between symbol and quasisymbol neurons as short-term memory, important role of synaptic plasticity in learning processes are confirmed numerically. Correctness of fundamental ideas put in base of conceptual model is confirmed on olfactory bulb at quantitative level.

Core Design Pattern for Efficient Multi-agent Architecture

Interaction engineering is fundamental for agent based systems. In this paper we will present a design pattern for the core of a multi-agent platform - the message communication and behavior activation mechanisms - using language features of C#. An agent platform is developed based on the pattern structure, which is legiti- mated through experiences of using JADE in real applications. Results of the communication model are compared against the popular JADE platform.

Improved Hybrid Model of HMM/GMM for Speech Recognition

In this paper, we propose a speech recognition engine using hybrid model of Hidden Markov Model (HMM) and Gaussian Mixture Model (GMM). Both the models have been trained independently and the respective likelihood values have been considered jointly and input to a decision logic which provides net likelihood as the output. This hybrid model has been compared with the HMM model. Training and testing has been done by using a database of 20 Hindi words spoken by 80 different speakers. Recognition rates achieved by normal HMM are 83.5% and it gets increased to 85% by using the hybrid approach of HMM and GMM.

Automated Software Reengineering Model and Framework

Тодор П. Чолаков, Димитър Й. Биров - Тази статия представя цялостен модел за автоматизиран реинженеринг на наследени системи. Тя описва в детайли процесите на превод на софтуера и на рефакторинг и степента, до която могат да се автоматизират тези процеси. По отношение на превода на код се представя модел за автоматизирано превеждане на код, съдържащ указатели и работа с адресна аритметика. Също така се дефинира рамка за процеса на реинженеринг и се набелязват възможности за по-нататъшно развитие на концепции, инструменти и алгоритми.

Detecting Precipitation Climate Changes: An Approach Based on a Stochastic Daily Precipitation Model

2002 Mathematics Subject Classification: 62M10.

Cognitive-didactic Model for Making Testing Items in Physics

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2015