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 9 of 9 for “"Neural network hardware"”.
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Inference neural network hardware acceleration techniques
… matrix multiplication. As a result, building a neural processing unit (NPU) beside the CPU to accelerate matrix multiplication is a popular approach. The NPU helps reduce the work done by the CPU, and often operates in parallel with the CPU, so in general, introducing the NPU gains performance. …
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Energy-Efficient Neural Network Hardware Design and Circuit Techniques to Enhance Hardware Security
Artificial intelligence (AI) algorithms and hardware are being developed at a rapid pace for emerging applications such as self-driving cars, speech/image/video recognition, deep learning, etc. Today’s AI tasks are mostly performed at remote datacenters, while in the future, more AI workloads are …
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Design, modeling, and simulation of a Compact Optoelectronic Neural Coprocessor
… Substantial research has focused on using neural network algorithms to process this type of data with much success. Most of this effort, however, has resulted in sophisticated neural network-based software algorithms rather than physical neural network hardware. Consequently, most neural …
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Direct Photon Differential Cross Section in p̄p Collisions at the Square Root of s = 1.8 TeV
… of the Central Preradiator Chambers, the neural network hardware trigger upgrades, and the six times increase in integrated luminosity. Two different methods, conversion method and profile method, were used to separate prompt photons from photons produced by decay of hadrons. The profile …
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A Deep Learning and Signal Processing Architecture Using Frequency-Encoded RF Photonics
Deep neural networks have become ubiquitous due to their ability to perform arbitrary tasks more accurately than manually-crafted systems. This ability has created a substantial demand for more complex models processing larger amounts of data. However, the traditional computing architecture has …
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Neural networks in control engineering
… is to investigate the viability of integrating neural networks into control structures. These networks are an attempt to create artificial intelligent systems with the ability to learn and remember. They mathematically model the biological structure of the brain and consist of a large number of …
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Hardware/Neural Network Codesign for Energy-Efficient Inference on Edge Devices with Optimal Mapping and Compression
L'abstract è presente nell'allegato / the abstract is in the attachment
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Accelerating Quantized DNNs with Dedicated Hardware Accelerators and RISC-V Processors Using Precision-Scalable Multipliers
L'abstract è presente nell'allegato / the abstract is in the attachment
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Development of machine learning based speaker recognition system
… we trained Support Vector Machine and Artificial Neural Network classifiers using “One vs. all” strategy. We tested our recognition models with unseen voice records from different speakers and found them very successful based on different criteria such as equal error rate, precision and recall …