Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 15 of 15 for “"neuromorphic hardware"”.
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Study and implementation of new computational paradigms exploiting neuromorphic hardware architectures
L'abstract è presente nell'allegato / the abstract is in the attachment
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Energy-Efficient Neuromorphic Hardware. Design and Optimization of Brain-Inspired Computing Paradigms for Spiking Neural Networks
L'abstract è presente nell'allegato / the abstract is in the attachment
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Inference and Learning in Spiking Neural Networks for Neuromorphic Systems
<p>Neuromorphic computing is a computing field that takes inspiration from the biological and physical characteristics of the neocortex system to motivate a new paradigm of highly parallel and distributed computing to take on the demands of the ever-increasing scale and computational complexity of …
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Inference And Learning In Spiking Neural Networks For Neuromorphic Systems
<p>Neuromorphic computing is a computing field that takes inspiration from the biological and physical characteristics of the neocortex system to motivate a new paradigm of highly parallel and distributed computing to take on the demands of the ever-increasing scale and computational complexity of …
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Active Pre-Touch Sensing: From Biology to Neuromorphic Biomimetic Artifacts
… for potential implementation in dedicated neuromorphic hardware. The technical perspective is incorporated at the neuronal level of the network, where neuron and synapse models reflect the idealized behavior of analogous implementations in neuromorphic hardware. The here implemented network …
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Large-scale neuromorphic computing hardware for analog AI enabled by epitaxial random access memory
A neuromorphic computing on memristor-based crossbars is one of promising next generation analog computing methods since it features fast switching speed, extremely small cell footprint, low energy consumption for matrix-vector multiplication, capability of both storage and computing, …
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Benefits of branches in sparsely connected networks
… require faster and lower power alternatives. Neuromorphic engineering promises speed and energy efficiency, yet these devices can have unique constraints making them difficult to train. Motivated by optoelectronic devices, a unique class of optics-based neuromorphic hardware such as the COIN …
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Development of Transition Metal Dichalcogenide Memristive Materials and Devices for Neuromorphic Systems
… for energy-efficient computing architectures. Neuromorphic engineering addresses this challenge by replicating the brain’s co-location of memory and computation in hardware. Transition metal dichalcogenides (TMDCs) are promising in this context, offering atomically thin scalability and …
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Spiking Neural Network with Memristive Based Computing-In-Memory Circuits and Architecture
In recent years neuromorphic computing systems have achieved a lot of success due to its ability to process data much faster and using much less power compared to traditional Von Neumann computing architectures. There are two main types of Artificial Neural Networks (ANNs), Feedforward Neural …
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Synthesis of neuromorphic circuits with neuromodulatory properties
The field of neuromorphic engineering shows great promise in delivering novel devices inspired by biological principles that would undertake sensory and processing tasks with an unprecedented level of efficiency. In order to achieve that, engineers are required to understand and implement the many …
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Adaptable Network Systems
… for bio-inspired network architectures, for both neuromorphic hardware design and materials-based network design.
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Energy-efficient Neuromorphic Computing for Resource-constrained Internet of Things Devices
… Of the various prospective avenues, the field of neuromorphic computing has garnered significant recognition as a crucial means to achieve fast and energy-efficient machine intelligence applications for IoT devices. The programming of neuromorphic computing hardware typically involves the …
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Efficient Processing of Spiking Neural Networks: A Memory-Based Approach
Neuromorphic systems have been developed with the aim of mimicking biological systems in terms of functionality and processing efficiency. Spiking neural networks (SNNs) are widely used as the computing model for the neuromorphic system. The neurons in the SNN communicate using spikes, which allows …
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Estudio e implementación de algoritmos de fusión sensorial para sensores pulsantes y clásicos con protocolo AER de comunicación y aplicación en sistemas robóticos neuroinspirados
… is made. The background of the thesis is the neuromorphic engineering field. This term was first coined in the late eighties by Caver Mead. Its main objective is to develop hardware devices, based on the neuron as the basic unit, to develop a range of tasks such as: decision making, image …
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Diseño e implementación de una red neuromórfica adaptativa para la generación y control de movimiento robótico bioinspirado
… su viabilidad. Posteriormente, se traslada al hardware neuromórfico de SpiNNaker, y se comparan los resultados entre el simulador y el hardware para verificar su similitud. Una vez confirmada su efectividad, se utiliza una FPGA para monitorizar la salida de la estructura neuronal y ajustar su …