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On the construction of artificial brains

Author: Ulrich Ramacher; Christoph von der Malsburg
Publisher: Berlin : Springer, ©2010.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
This book presents a first generation of artificial brains, using vision as sample application. An object recognition system is built, using neurons and synapses as exclusive building elements. The system contains a feature pyramid with 8 orientations and 5 resolution levels for 1000 objects and networks for binding of features into objects. This vision system can recognize objects robustly in the presence of  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
On the construction of artificial brains.
Berlin : Springer, ©2010
(OCoLC)465370488
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Ulrich Ramacher; Christoph von der Malsburg
ISBN: 9783642001895 3642001890
OCLC Number: 663097555
Description: 1 online resource (viii, 359 pages) : illustrations
Contents: Cover --
Contents --
Prologue --
0.1 Main Results --
0.2 Prehistory of Our Project --
0.3 Acknowledgement --
1 The Difficulty of Modelling Artificial Brains --
1.1 McCullogh-Pitts Model --
1.2 Learning Nets --
1.3 Spiking Neurons --
1.4 Architecture of Vision --
1.5 The Steps of the Construction Process --
1.6 Summary --
2 Information Processing in Nets with Constant Synapses --
2.1 Generic Signal Equations for Pulse Neurons and Synapses --
2.2 Partitions and Their Time Development --
2.3 Experiments with Constant Synapses --
2.4 Entropy and Transfer Function of a Net --
2.5 Operating Range of a Net --
2.6 Pulse Rates --
2.7 Resolution and Net Size --
2.8 Application Potential --
2.9 Limited Simulation Time --
2.10 Summary --
3 Theory of Nets with Constant or Dynamic Synapses --
3.1 Derivation of the Signal Energy --
3.2 Temporal Mean and Spatial Mean --
3.3 Determination of the Frequency Distribution --
3.4 Summary --
4 Macro-Dynamics of Nets with Constant Synapses --
4.1 Known Synapses --
4.2 Known Distribution of Synapses --
4.3 Agreement of Theory with Experiment --
4.4 Lack of Correlation --
4.5 Determining the Signal Energy and Entropy by Pulse Rates --
4.6 Summary --
5 Information Processing with Dynamic Synapses --
5.1 The Types of Solutions of Synaptic Equations --
5.2 Synchronisation of Neurons --
5.3 Segmentation per Synchronisation --
5.4 Calculation of Pulse Differences and Sums --
5.5 Simple Applications --
5.6 Time Coding and Correlation --
5.7 Entropy and State Space --
5.8 Preliminary Considerations on the Statistics of Synchronisation --
5.9 Summary --
6 Nets for Feature Detection --
6.1 Overview of Visual System --
6.2 Simple Cells --
6.3 Creation of Detector Profiles for Gabor Wavelets --
6.4 Experimental Check --
6.5 Summary --
7 Nets for Feature Recognition --
7.1 Principles of Object Recognition --
7.2 Net Architecture for Robust Feature Recognition --
7.3 Feature Recogniser --
7.4 Selectivity --
7.5 Orthogonality of Rotation --
7.6 Invariance of Function as to Brightness --
7.7 Invariance of Function as to Form and Mimic --
7.8 Generating Object Components through Binding of Features --
7.9 Summary --
8 Nets for Robust Head Detection --
8.1 Results of Head Detection --
8.2 Next Steps --
8.3 Summary --
9 Extensions of the Vision Architecture --
9.1 Distance-Invariant Feature Pyramid --
9.2 The Inner Screen --
9.3 Summary --
10 Look-out --
10.1 Data Format of the Brain --
10.2 Self-Organisation --
10.3 Learning --
10.4 Invariant Object Recognition --
10.5 Structured Memory Domains --
10.6 Summary --
11 Preliminary Considerations on the Microelectronic Implementation --
11.1 Equivalent Representations --
11.2 Microelectronic Implementations --
11.3 Models of Neurons and Synapses --
12 Elementary Circuits for Neurons, Synapses, and Photosensors --
12.1 Neuron --
12.2 Adaptive Synapses --
12.3 Photosensors --
12.4 DA-Converters and Analogue Image Storage --
12.5 Summary --
13 Simulation of Microelectronic Neural Circuits and Systems --
13.1 Modelling of Neurons and Synapses --
13.2 Results of Modelling --
13.3 Notes on the Simulation Procedure --
13.4 Summary --
14 Architecture and Chip Design of the Feature Recognizer --
14.1 Chip Architecture of the Feature Recogni.
Responsibility: Ulrich Ramacher, Christoph von der Malsburg, eds.

Abstract:

This well structured, interdisciplinary and introductory book on artificial brains presents the neurocomputer of the second generation. It uses experiment, theory and implementation in a balanced new  Read more...

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