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 7 of 7 for “"Dynamic Neural Network"”.
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Dynamic Neural Network for Efficient Video Recognition
… The amount of redundancy largely depends on the dynamics and events captured in the video. For example, static videos typically have more temporal redundancy, while videos focusing on objects tend to have more channel redundancy. To address this challenge, we propose a novel approach that reduces …
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Dynamic Neural Network-based Adaptive Inverse Optimal Control Design
This dissertation introduces a Dynamical Neural Network (DNN) model based adaptive inverse optimal control design for a class of nonlinear systems. A DNN structure is developed and stabilized based on a control Lyapunov function (CLF). The CLF must satisfy the partial Hamilton Jacobi-Bellman (HJB) …
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Mechanisms of Sensory Adaptation in the Primate Visual System
… impinging on the retina varies within a dynamic range of 220 dB. Stimulus contrast can also vary drastically within a scene, and eye movements leave little time for sampling luminance. In addition, the amount of information reaching our visual system far exceeds the brain’s information …
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DYNAMIC SELF-ORGANISED NEURAL NETWORK INSPIRED BY THE IMMUNE ALGORITHM FOR FINANCIAL TIME SERIES PREDICTION AND MEDICAL DATA CLASSIFICATION
Artificial neural networks have been proposed as useful tools in time series analysis in a variety of applications. They are capable of providing good solutions for a variety of problems, including classification and prediction. However, for time series analysis, it must be taken into account that …
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Investigation in modeling a load-sensing pump using dynamic neural unit based dynamic neural networks
… so much of concern in the “black box” approach. Neural network can be used to implement the black box concept for system identification and it is proven that the neural network have the ability to model very complex behaviour and there is a well defined set of neural and neural network …
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Design-Space Exploration of Biologically-Inspired SNN Models for Application-Specific Many-Core Systems
In recent years, Spiking Neural Networks (SNNs) have drawn significant attention as a promising route for advancing machine learning models. SNNs are different from traditional neural network architectures in that they replicate the spiking behavior of biological neurons. This research study …
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Dynamic Neural Networks and Brain-inspired Computing
L'abstract è presente nell'allegato / the abstract is in the attachment