During the first years after the introduction of the CNN paradigm, many templates were designed by cut-and-try techniques, playing with a few nonzero template elements, and using a simulator to calculate the CNN dynamics. After a while, some systematic design methodologies emerged. Today several methods are available for generating CNN templates or algorithms, even for complex tasks.

Various design techniques

The main classes of design techniques are as follows:

• systematic methods for binary I/O function via Boolean description and decomposition techniques using uncoupled CNN (see Chapters 5, 6, 7)

• systematic methods for binary I/O function using coupled CNN (see also Chapter 12)

• global optimization techniques as parameter optimization

• genetic algorithms for designing the template elements/synaptic weights

• matching with the spatially discrete representations of partial differential equations (PDEs)

• matching with some neuromorphic models of a living organism, typically the nervous system, in particular the visual pathway of vertebrates (see Chapter 16)

• fuzzy design techniques

• neural network techniques

• matching with existing 2D or 3D algorithms, including techniques in signal processing, telecommunications, adaptive control, nonlinear spatio-temporal dynamical systems, etc.

We have to emphasize, however, that, in spite of the many design techniques, new methods are emerging day by day based on the intuition and skill of the designers. A good example for this is a recent method using active waves applied for a while and combining/colliding with other waves, as well as a method in which a wave metric is used for complex pattern recognition tasks.