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Classroom Contents
TinyML Talks - The New Neuromorphic Analog Signal Processor Concept and Technology Platform
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- 1 Introduction
- 2 About tinyML
- 3 Core of technology
- 4 Physical layout
- 5 Design flow
- 6 Business model
- 7 Product line
- 8 Human Activity Recognition
- 9 Digital Fingerprint
- 10 Narrow Voice
- 11 Data Transfer
- 12 Partnership
- 13 Can you elaborate further on how the train neural network is converted to an AP
- 14 Can resistors representing weights be reprogrammed
- 15 Analog arrays vs gate arrays
- 16 Job opportunities
- 17 Typical number of neural network parameters
- 18 How is neural sense better than noise cancellation
- 19 Can neural net recognize music
- 20 Is the digital imprint application agnostic
- 21 Is there any correlation to neuromorphic processors
- 22 How can we use these models
- 23 What kind of tools can we use
- 24 Simulations
- 25 Direct sensor to spike converters
- 26 Publications
- 27 Mismatch
- 28 More questions
- 29 Precision
- 30 Conclusion
- 31 Strategic Partners
