Tiivistelmä List of abbreviations List of symbols

This research paper presents Neuro-Fuzzy applications to Moving Picture Expert Group (MPEG-4) video transmission in IEEE 802.15.4 ZigBee wireless. ZigBee can operate within 2.4 GHz frequency with a data rate of 250 kb/s, which may interfere with other wireless devices functioning within the same frequency band such as WiFi and Bluetooth. MPEG-4 Variable Bit Rate (VBR) video demands large bandwi...

As demand for high quality transmission increases, improving spectrum efficiency and error performance in wireless communication systems are important. OFDM is a multi-carrier modulation technique with densely spaced sub-carriers that has gained a lot of popularity among the broadband community in the last few years. One of the promising approaches to next generation communication systems are a...

the oxidative coupling of methane (ocm) performance over na-w-mn/sio2 at elevated pressures has been simulated by adaptive neuro fuzzy inference system (anfis) using reaction data gathered in an isothermal fixed bed microreactor. in the designed neuro fuzzy models, three important parameters such as methane to oxygen ratio, gas hourly space velocity (ghsv), and reaction temperature were conside...

In this paper we present a new class of neuro-fuzzy systems designed for system modelling and pattern classification. Our approach is characterized by automatic determination of fuzzy inference in the process of learning. Moreover, we introduce several flexibility concepts in the design of neuro-fuzzy systems. The method presented in the paper is characterized by high accuracy which outperforms...

The design and optimization process of fuzzy controllers can be supported by learning techniques derived from neural networks. Such approaches are usually called neuro-fuzzy systems. In this paper, we describe the application of an updated version of the neuro-fuzzy model NEFCON to a real plant. The NEFCON model is able to learn and optimize the rulebase of a Mamdani-type fuzzy controller onlin...

Neuro-fuzzy networks have been successfully applied to extract knowledge from data in the form of fuzzy rules. However, one drawback with the neuro-fuzzy approach is that the fuzzy rules induced by the learning process are not necessarily understandable. The lack of readability is essentially due to the high dimensionality of the parameter space that leads to excessive flexibility in the modifi...

This paper comprises two parts, the first deals with the conception of a class of Hybrid Granular Min-Max Fuzzy-Neuro Relational Learners, for which a learning scheme was devised that uses an exhaustive search over the fuzzy partitions of involved variables, automatic fuzzy hypotheses generation, formulation and testing, and successive approximation procedure of Min-Max relational equations. Th...