Sökning: "Brain Like Computing"
Visar resultat 1 - 5 av 8 avhandlingar innehållade orden Brain Like Computing.
1. Self-Knowledge/Self-Regulation/Self-Control: A Ubiquitous Computing Perspective
Sammanfattning : This thesis is about self-knowledge, self-regulation and self-control. All three of these terms are easily understandable, and apply to situations in our daily lives (like misjudging one’s own competence at retiling the bathroom floor, or feeling the anxiety and thrill of doing unsupervised work, or guiltily hitting the snooze-button for the fifth time, and missing half a day of school). LÄS MER
2. Event-Driven Architectures for Heterogeneous Neuromorphic Computing Systems
Sammanfattning : Mixed-signal neuromorphic processors have brain-like organization and device physics optimized for emulation of spiking neural networks (SNNs), and offer an energy-efficient alternative for implementing artificial intelligence in applications where deep learning based on conventional digital computing is unfeasible or unsustainable. However, efficient use of such hardware requires appropriate configuration of its inhomogeneous, analog neurosynaptic circuits, with methods for sparse, spike-timing-based information encoding and processing. LÄS MER
3. Computational Models in Deep Brain Stimulation : Patient‐Specific Simulations, Tractography, and Group Analysis
Sammanfattning : Deep brain stimulation (DBS) is an established method for symptom relief in movement disorders like Parkinson’s disease, essential tremor (ET), and dystonia. The therapy is based on implanting an electrode with four contacts in the deep brain structures where it provides electrical stimulation, mainly impacting the nerve tracts. LÄS MER
4. SiLago: Enabling System Level Automation Methodology to Design Custom High-Performance Computing Platforms : Toward Next Generation Hardware Synthesis Methodologies
Sammanfattning : .... LÄS MER
5. An Attractor Memory Model of Neocortex
Sammanfattning : This thesis presents an abstract model of the mammalian neocortex. The model was constructed by taking a top-down view on the cortex, where it is assumed that cortex to a first approximation works as a system with attractor dynamics. LÄS MER