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Full-Text Articles in Engineering
Early Emerging Pathogen Detection, Mackenzie Wangenstein
Early Emerging Pathogen Detection, Mackenzie Wangenstein
Undergraduate Research & Mentoring Program
A supervised learning technique was employed to identify emerging pathogen species. Portland State University has partnered with the University of New Mexico to take encodings of unknown pathogen molecular structures to determine emerging species.
Computational Capabilities Of Leaky Integrate-And-Fire Neural Networks For Liquid State Machines, Amin Almassian, Christof Teuscher
Computational Capabilities Of Leaky Integrate-And-Fire Neural Networks For Liquid State Machines, Amin Almassian, Christof Teuscher
Student Research Symposium
We analyze the computational capability of Leaky Integrate-and-Fire (LIF) Neural Networks used as a reservoir (liquid) in the framework of Liquid State Machines (LSM). Maass et. al. investigated LIF neurons in LSM and their results showed that they are capable of noise-robust, parallel, and real-time computation. However, it still remains an open question how the network topology affects the computational capability of a reservoir. To address that question, we investigate the performance of the reservoir as a function of the average reservoir connectivity. We also show that the dynamics of the LIF reservoir is sensitive to changes in the average …
Pulse Coupled Neural Networks For The Segmentation Of Magnetic Resonance Brain Images, Shane L. Abrahamson
Pulse Coupled Neural Networks For The Segmentation Of Magnetic Resonance Brain Images, Shane L. Abrahamson
Theses and Dissertations
This research develops an automated method for segmenting Magnetic Resonance (MR) brain images based on Pulse Coupled Neural Networks (PCNN). MR brain image segmentation has proven difficult, primarily due to scanning artifacts such as interscan and intrascan intensity inhomogeneities. The method developed and presented here uses a PCNN to both filter and segment MR brain images. The technique begins by preprocessing images with a PCNN filter to reduce scanning artifacts. Images are then contrast enhanced via histogram equalization. Finally, a PCNN is used to segment the images to arrive at the final result. Modifications to the original PCNN model are …