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The Roots of Backpropagation: From Ordered Derivatives to Neural Networks and Political Forecasting (Adaptive and Cognitive Dynamic Systems: Signal Processing #1)
Description
Now, for the first time, publication of the landmark work inbackpropagation Scientists, engineers, statisticians, operationsresearchers, and other investigators involved in neural networkshave long sought direct access to Paul Werbos's groundbreaking, much-cited 1974 Harvard doctoral thesis, The Roots ofBackpropagation, which laid the foundation of backpropagation. Now, with the publication of its full text, these practitioners can gostraight to the original material and gain a deeper, practicalunderstanding of this unique mathematical approach to socialstudies and related fields. In addition, Werbos has provided threemore recent research papers, which were inspired by his originalwork, and a new guide to the field. Originally written for readerswho lacked any knowledge of neural nets, The Roots ofBackpropagation firmly established both its historical andcontinuing significance as it:
* Demonstrates the ongoing value and new potential ofbackpropagation
* Creates a wealth of sound mathematical tools useful acrossdisciplines
* Sets the stage for the emerging area of fast automaticdifferentiation
* Describes new designs for forecasting and control which exploitbackpropagation
* Unifies concepts from Freud, Jung, biologists, and others into anew mathematical picture of the human mind and how it works
* Certifies the viability of Deutsch's model of nationalism as apredictive tool--as well as the utility of extensions of thiscentral paradigm
"What a delight it was to see Paul Werbos rediscover Freud'sversion of 'back-propagation.' Freud was adamant (in The Projectfor a Scientific Psychology) that selective learning could onlytake place if the presynaptic neuron was as influenced as is thepostsynaptic neuron during excitation. Such activation of bothsides of the contact barrier (Freud's name for the synapse) wasaccomplished by reducing synaptic resistance by the absorption of'energy' at the synaptic membranes. Not bad for 1895 But Werbos1993 is even better." --Karl H. Pribram Professor Emeritus, Stanford University.
Other Books in Series
Impact of Attention on Perception in Cognitive Dynamic Systems (Adaptive and Cognitive Dynamic Systems: Signal Processing)
Acoustic Echo and Noise Control: A Practical Approach (Adaptive and Cognitive Dynamic Systems: Signal Processing #40)
Intelligent Image Processing (Adaptive and Cognitive Dynamic Systems: Signal Processing #27)
Nonlinear and Adaptive Control Design (Adaptive and Cognitive Dynamic Systems: Signal Processing #7)
Bayesian Signal Processing: Classical, Modern, and Particle Filtering Methods (Adaptive and Cognitive Dynamic Systems: Signal Processing #54)
Kernel Adaptive Filtering (Adaptive and Cognitive Dynamic Systems: Signal Processing #57)
Principal Component Neural Networks: Theory and Applications (Adaptive and Cognitive Dynamic Systems: Signal Processing #4)
Robust Systems Theory and Applications (Adaptive and Cognitive Dynamic Systems: Signal Processing #12)
Space-Time Layered Information Processing for Wireless Communications (Adaptive and Cognitive Dynamic Systems: Signal Processing #30)
Data Variant Kernel Analysis (Adaptive and Cognitive Dynamic Systems: Signal Processing)
Stable Adaptive Control and Estimation for Nonlinear Systems: Neural and Fuzzy Approximator Techniques (Adaptive and Cognitive Dynamic Systems: Signal Processing #28)
Fuzzy and Neural Approaches in Engineering (Adaptive and Cognitive Dynamic Systems: Signal Processing #10)
Least-Mean-Square Adaptive Filters (Adaptive and Cognitive Dynamic Systems: Signal Processing #31)
Recurrent Neural Networks for Prediction: Learning Algorithms, Architectures and Stability (Adaptive and Cognitive Dynamic Systems: Signal Processing)
Kalman Filtering and Neural Networks (Adaptive and Cognitive Dynamic Systems: Signal Processing #23)
Unsupervised Adaptive Filtering, Blind Deconvolution (Adaptive and Cognitive Dynamic Systems: Signal Processing #24)
Radio Resource Management (Adaptive and Cognitive Dynamic Systems: Signal Processing)
Correlative Learning: A Basis for Brain and Adaptive Systems (Adaptive and Cognitive Dynamic Systems: Signal Processing #49)
