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Neural networks for electronics hobbyists : a non-technical project-based introduction /
"Learn how to implement and build a neural network with this non-technical, project-based book as your guide. As you work through the chapters, you'll build an electronics project, providing a hands-on experience in training a network. There are no prerequisites here and you won't see...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
California :
Apress,
[2018]
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Intro; Table of Contents; About the Author; About the Technical Reviewer; Preface; Chapter 1: Biological Neural Networks; Biological Computing: The Neuron; What Did You Do to Me?; Wetware, Software, and Hardware; Wetware: The Biological Computer; Software: Programs Running on a Computer; Hardware: Electronic Circuits; Applications; Just Around the Corner; Chapter 2: Implementing Neural Networks; Architecture?; A Variety of Models; Our Sample Network; The Input Layer; The Hidden Layer; The Output Layer; Training the Network; Summary; Chapter 3: Electronic Components; What Is XOR?
- The ProtoboardThe Power Supply; Inputs; SPDT Switches; Resistor Color Code; LEDs; What Is a Voltage Divider?; Adjusting Connection Weights; Summing Voltages; Op Amp Comparator; Putting It All Together; Parts List; Summary; Chapter 4: Building the Network; Do We Need a Neural Network?; The Power Supply; The Input Layer; The Hidden Layer; Installing potentiometers and Op Amps; Installing Input Signals to the Op Amps; The Output Layer; Installing Potentiometers and Op Amp Z; Installing Inputs to Op Amp Z; Finishing the Output Layer; Testing the circuit; Summary.
- Chapter 5: Training with Back PropagationThe Back Propagation Algorithm; Implementing the Back Propagation Algorithm; Training Cycles; Convergence; Attractors and Trends; What Is an Attractor?; Attractors in Our Trained Networks; Implementation; Summary; Chapter 6: Training on Other Functions; The OR Function; The AND Function; The General Purpose Machine; Summary; Chapter 7: Where Do We Go from Here?; Varying the Learning Rate; Crazy Starting Values; Apply the Back Propagation Rule Differently; Feature Extraction; Determining the Range of Values; Training on Different Logic Functions.
- Try Using a Different ModelBuild a Neural Network to Do Other Things; Postscript; Summary; Appendix A: Neural Network Software, Simbrain; Appendix B: Resources; Neural Network Books; Chaos and Dynamic Systems; Index.