FACULTY OF ENGINEERING, SCIENCE AND MATHEMATICS SCHOOL OF ELECTRONICS AND COMPUTER SCIENCE Doctor of Philosophy MUTUAL FEATURES FOR PATTERN CLASSIFICATION by Heiko Claussen The mean of a data set is one trivial representation of data from one class. This thesis discusses mutual interdependence analysis (MIA) that is successfully used to extract more involved representations, or “mutual features...

Geo-security, or location-based security service, provides authorization of persons or facilities based on their distinctive location information. It applies the field of position navigation and time (PNT) to the provision of security. Location-dependent parameters from radio navigation signals are quantized to compute a location verification tag or “geotag” to block or allow accesses by users....

This paper describes a method of constructing one-hidden layer feedforward linear threshold networks to represent Boolean functions (or partially-defined Boolean functions). The first step in the construction is sequential linear separation, a technique that has been used by a number of researchers [7, 11, 2]. Next, from a suitable sequence of linear separations, a threshold network is formed. ...

The nearest neighbor method is one of the most widely used pattern classificationmethods. However its major drawback in practice is the curse of dimensionality. In this paper we propose a new method to alleviate this problem significantly. In this method, we attempt to cover the training patterns of each class with a number of hyperspheres. The method attempts to design hyperspheres as compact ...

Background: Osteoporosis is a systemic skeletal disease characterized by low bone mineral density (BMD) and micro-architectural deterioration of bone tissue, leading to bone fragility and increased fracture risk. Since Panoramic image is a feasible and relatively routine imaging technique in dentistry; it could provide an opportunistic chance for screening osteoporosis. In this regard, numerous...

This work presents a technique for the analysis of Facial Electromyogram signal activities to classify five different facial expressions for Computer-Muscle Interfacing applications. Facial Electromyogram (FEMG) is a technique for recording the asynchronous activation of neuronal inside the face muscles with non-invasive electrodes. FEMG pattern recognition is a difficult task for the researche...