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Full-Text Articles in Signal Processing
Least Squares Support Vector Machine Based Classification Of Abnormalities In Brain Mr Images, S. Thamarai Selvi, D. Selvathi, R. Ramkumar, Henry Selvaraj
Least Squares Support Vector Machine Based Classification Of Abnormalities In Brain Mr Images, S. Thamarai Selvi, D. Selvathi, R. Ramkumar, Henry Selvaraj
Electrical & Computer Engineering Faculty Research
The manual interpretation of MRI slices based on visual examination by radiologist/physician may lead to missing diagnosis when a large number of MRIs are analyzed. To avoid the human error, an automated intelligent classification system is proposed. This research paper proposes an intelligent classification technique to the problem of classifying four types of brain abnormalities viz. Metastases, Meningiomas, Gliomas, and Astrocytomas. The abnormalities are classified based on Two/Three/ Four class classification using statistical and textural features. In this work, classification techniques based on Least Squares Support Vector Machine (LS-SVM) using textural features computed from the MR images of patient are …
Supplementing An Ad-Hoc Wireless Network Routing Protocol With Radio Frequency Identification (Rfid) Tags, Leroy S. Willemsen
Supplementing An Ad-Hoc Wireless Network Routing Protocol With Radio Frequency Identification (Rfid) Tags, Leroy S. Willemsen
Theses and Dissertations
Wireless sensor networks (WSNs) have a broad and varied range of applications, yet all of these are limited by the resources available to the sensor nodes that make up the WSN. The most significant resource is energy. A WSN may be deployed to an inhospitable or unreachable area, leaving it with a non-replenishable power source. This research examines a way of reducing energy consumption by augmenting the nodes with radio frequency identification (RFID) tags that contain routing information. It was expected that RFID tags would reduce the network throughput, the ad hoc on-demand distance vector (AODV) routing traffic sent, and …
Characterization And Design Of High-Level Vhdl I/Q Frequency Downconverter Via Special Sampling Scheme, Jesse P. Somann
Characterization And Design Of High-Level Vhdl I/Q Frequency Downconverter Via Special Sampling Scheme, Jesse P. Somann
Theses and Dissertations
This study explores the characterization and implementation of a Special Sampling Scheme (SSS) for In-Phase and Quad-Phase (I/Q) down conversion utilizing top-level, portable design strategies. The SSS is an under-developed signal sampling methodology that can be used with military and industry receiver systems, specifically, United States Air Force (USAF) video receiver systems. The SSS processes a digital input signal-stream sampled at a specified sampling frequency, and down converts it into In-Phase (I) and Quad-Phase (Q) output signal-streams. Using the theory and application of the SSS, there are three main objectives that will be accomplished: characterization of the effects of input, …