Towards Neuromorphic Machine Intelligence
Spike-Based Representation, Learning, and Applications
- 1st Edition - August 1, 2024
- Author: Hong Qu
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 3 2 8 2 0 - 6
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 3 2 8 2 1 - 3
Towards Neuromorphic Machine Intelligence: Spike-Based Representation, Learning and Applications provides readers with in-depth understanding of Spiking Neural Networks (SNN),… Read more
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Request a sales quote2. Fundamentals of Spiking Neural Networks
3. Specialized Spiking Neuron Model
4. Learning Algorithms for Shallow Spiking Neural Networks
5. Learning Algorithms for Deep Spiking Neural Networks
6. Neural Column-Inspired Spiking neural networks
7. Retinal-Inspired Visual Spiking Neural Network
8. ANN-SNN Algorithm Suitable for Ultra Energy Efficient Application
9. Neuromorphic Hardware
10. Conclusions
- No. of pages: 250
- Language: English
- Edition: 1
- Published: August 1, 2024
- Imprint: Academic Press
- Paperback ISBN: 9780443328206
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Hong Qu
Dr. Hong Qu received the Ph.D. degree in computer science from the University of Electronic Science and Technology of China, Chengdu, China, in 2006. From 2007 to 2008, he was a Post-Doctoral Fellow with the Advanced Robotics and Intelligent Systems Laboratory, School of Engineering, University of Guelph, Guelph, ON, Canada. From 2014 to 2015, he was a Visiting Scholar with the Potsdam Institute for Climate Impact Research, Potsdam, Germany, and the Humboldt University of Berlin, Berlin, Germany. He is currently a Professor with the Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China. His current research interests include neural networks, machine learning, and big data.