edited by Ronald Tetzlaff (Johann Wolfgang Goethe-University, Germany)

This volume covers the fundamental theory of Cellular Neural Networks as well as their applications in various fields such as science and technology. It contains all 83 papers of the 7th International Workshop on Cellular Neural Networks and their Applications. The workshop follows a biennial series of six workshops consecutively hosted in Budapest (1990), Munich, Rome, Seville, London and Catania (2000).

• On the Relationship Between CNNs and PDEs (M Gilli et al.)
• Moving Object Tracking on Panoramic Images (P Földesy et al.)
• Emergence of Global Patterns in Connected Neural Networks (T Shimizu)
• Configurable Multi-Layer CNN-UM Emulator on FPGA (Z Nagy & P Szolgay)
• A CNN Based System to Blind Sources Separation of MEG Signals (M Bucolo et al.)
• Time as Coding Space for Information Processing in the Cerebral Cortex (W Singer)
• Analyzing Multidimensional Neural Activity via CNN-UM (V Gál et al.)
• Visual Feedback by Using a CNN Chip Prototype System (P Arena et al.)
• Computational and Computer Complexity of Analogic Cellular Wave Computers (T Roska)
• Chaotic Phenomena in Quantum Cellular Neural Networks (L Fortuna & D Porto)
• Fingerprint Image Enhancement Using CNN Gabor-Type Filters (E Saatci & V Tavsanoglu)
• CNN Based Color Constancy Algorithm (L Török & Á Zarándy)
• Statistical Error Modeling of CNN-UM Architectures: The Grayscale Case (P Földesy)
• MEMS, Microsystems and Nanosystems (M E Zaghloul)
• Texture Segmentation by the 64x64 CNN Chip (T Szirányi)
• Teaching CNN and Learning by Using CNN (P Arena et al.)
• Novel Methods and Results in Training Universal Multi-Nested Neurons (R Dogaru et al.)
• Test-Bed Board for 16x64 Stereo Vision CNN Chip (M Salerno et al.)
• and other papers