The present paper describes a feature extraction method based on -band wavelet packet frames for segmenting remotely sensed images. These wavelet features are then evaluated and selected using an efficient neurofuzzy algorithm. Both the feature extraction and neurofuzzy feature evaluation methods are unsupervised, and they do not require the knowledge of the number and distribution of classes c...

This paper focuses on the indirect adaptive tracking control of renewable energy sources in a grid-connected hybrid power system. The renewable energy systems have low efficiency and intermittent nature due to unpredictable meteorological conditions. The domestic load and the conventional charging stations behave in an uncertain manner. To operate the renewable energy sources efficiently for ha...

Extracting and validating emotional cues through analysis of users' facial expressions is of high importance for improving the level of interaction in man machine communication systems. Extraction of appropriate facial features and consequent recognition of the user's emotional state that can be robust to facial expression variations among different users is the topic of this paper. Facial anim...

In this paper, we propose a novel approach to reason with spatial proximity. The approach is based on contextual information and uses a neurofuzzy classifier to handle the uncertainty aspect of proximity. Neurofuzzy systems are a combination of neural networks and fuzzy systems and incorporate the advantages of both techniques. Although fuzzy systems are focused on knowledge representation, the...

This paper presents an efficient hybrid neurofuzzy control scheme for synchronous generator. The scheme proves to be beneficial as the control scheme targets for the better control of Synchronous generator when used along with other sub systems. The system is stabilize after t=0.13. The control parameter the performances indices of IAE are 4.755 for fuzzy and 7.242 for hybrid neuro fuzzy and fo...

In this paper, intelligent perception-based systems are proposed in application to medical diagnosis problems. The systems are created by use of connectionist neurofuzzy architectures that reflect fuzzy IFTHEN rules. The perception-based rules can be generated from examples by the system. Fuzzy reasoning, according to these rules, is considered within the framework of the computational theory o...

This paper describes, in a neurofuzzy framework, a method for the classification of different modes of radiowave propagation, followed by generation of linguistic rules justifying a decision. Weight decay during neural learning helps in imposing a structure on the network, resulting in the extraction of logical rules. Use of linguistic terms at the input enables better human interpretation of t...

This paper introduces a new approach to adjust a class of neurofuzzy networks based on the idea of participatory learning. Participatory learning is a mean to learn and revise beliefs based on what is already known or believed. The performance of the approach is verified with the Box and Jenkins gas furnace modeling problem, and with a shortterm load forecasting problem using actual data. Compa...