X-ray luggage inspection systems play an important role in ensuring air travelers' security. However, the false alarm rate of commercial systems can be as high as 20% due to less than perfect image processing algo...
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The Self-Organizing Map (SOM) is an efficient tool for visualizing high-dimensional data as it performs a topology-preserving projection of the input space on a low-dimensional grid. To utilize the information provide...
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Fault classification based upon vibration data is an essential building block of a sophisticated conditional based monitoring (CBM) system. Multiple sensor channels are called for to assure the redundancy and to achie...
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This paper presents the gait pattern generation work performed for the sixlegged robot EA308 developed in our laboratory. The aim is to achieve a dynamically developing gait pattern generation structure using reinforc...
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This paper presents the design, implementation and experiences of a new three hour experimental course taught for a joint undergraduate and graduate class at the University of Missouri-Rolla, USA. This course is uniqu...
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This paper presents the design, implementation and experiences of a new three hour experimental course taught for a joint undergraduate and graduate class at the University of Missouri-Rolla, USA. This course is unique in the sense that it covers the four main paradigms of Computational Intelligence (CI) and their integration to develop hybrid algorithms. The paradigms covered are artificial neural networks (ANNs), evolutionary computing (EC), swarm intelligence (SI) and fuzzy systems (FS). While individual CI paradigms have been applied successfully to solve real-world problems, the current trend is to develop hybrids of paradigms, since no one paradigm is superior to the others in all situations. In doing so, we are able capitalize on the respective strengths of the components of the hybrid CI system and eliminate weakness of individual components. This course is an introductory level course and will lead students to courses focused in depth in a particular paradigm (ANNs, EC, FS, SI). The idea of an integrated course like this is to expose students to different CI paradigms at an early stage in their degree program. The paper presents the course curriculum, tools used in teaching the course and how the assessments of the students' learning were carried out in this course.
Swarm intelligence algorithms are based on natural behaviors. Particle swarm optimization (PSO) is a stochastic search and optimization tool. Changes in the PSO parameters, namely the inertia weight and the cognitive ...
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Quantization is a crucial link in the process of digital speech communication. Non-uniform quantizer such as the logarithm quantizers are commonly used in practice. In this paper, a companding non-uniform quantizer is...
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This paper presents a wide area monitoring and protection technique based on a Learning Vector Quantization (LVQ) neural network. Phasor measurements of the power network buses are monitored continuously by a LVQ netw...
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With deregulation of the power industry, many tie lines between control areas are driven to operate near their maximum capacity, especially those serving heavy load centers. Wide area control systems (WACSs) using wid...
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This paper presents the design of a companding non-uniform optimal scalar quantizer for speech coding. The quantizer is designed using two neural networks to perform the nonlinear transformation. These neural networks...
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