A Cellular Neural Network (CNN) is the core circuitry behind our pattern generation for bipedal locomotion. The following papers will help you understand the basics of a CNN:

1. Cellular Neural Networks: Theory (File size: 1 MB). Chua, Leon O. and Yang, Lin. IEEE Transactions on Circuits and Systems, Vol. 35, No. 10, October 1988.
2. The CNN Paradigm (File size: 724 KB). Chua, Leon O. and Roska, Tamas. IEEE Transactions on Circuits and Systems - I: Fundamental Theory and Applications. Vol. 40., No. 3, March 1993.
3. Cellular Neural Networks with Nonlinear and Delay-Type Template Elements (File size: 478 KB). Chua, Leon O. and Roska, Tamas.

Please note: the CNN is used to generate the patterns (walking, running etc) for locomotion. It does NOT do anything else (like guarantee dynamic stability). However, by using a CNN we have eliminated the need to generate a locomotion pattern. Once we decide on a suitable locomotion pattern, we can design a suitable control law.