In this paper we introduce a new "neural" network for pattern recognition based on a gradient system. It is not, however, attempted to model any known behavior of biological neurons. This network stores any number of non-binary patterns (as its limit points) and retrieves them by associative recall. The network does not suffer from erroneous limit points. A realization of the network is given, which have heavily interconnected computing units. Finally two network examples are discussed.