During the same period an innovative line of research was actively developing with the efforts of Doctor of Technical Science E.M. Kussul. It concerned using stochastic methods to model assembly neuron-like networks. E.M. Kussul has put forward and analyzed a new neural network paradigm, which enabled to create neuron-like structures of great versatility. These structures are known as associative-projective neuron-like networks.
In mid-1908s a new term appeared in the field of human brain modeling - "neurocomputer". It essentially marked a new wave of research and development in the field of neural network methods of information processing, and almost completely replaced the term "neurocybernetics". The hopes put on early AI systems creation projects were naturally transferred onto neurocomputers, which were perceived of, in a broad sense, as prototypes of an "artificial brain" - an intelligent system supposed to be built and to function analogously to the human brain. The prefix "neuro" stressed the distinction of such a system from a traditional computer, as well as the functional proximity to the brain.
The actual state of affairs has fairly quickly forced to narrow down the meaning of the term "neurocomputer" to identifying it with artificial neural networks. Most of present research utilizes this term (or the term "neurocomputer") to indicate the whole range of research work within the approach to AI system development that is based on modeling of elements, structures, interactions and functions of different nervous system levels. In the modern sense, neurocomputer is a specialized software- or hardware-implemented computing device, which imitates the neural network operation.
The first hardware-based neurocomputer in USSR was developed in 1988-1989 on the basis of stochastic assembly neural network ideology. Research was carried out under the supervision of the Doctor of Technical Science E.M. Kussul, to whom Nikolai Mikhailovitch had already handed the Department over. The first neurocomputer prototype (1989), built on domestic element base, was a personal computer add-on. In subsequent prototypes, a more advanced element base was used. In 1992, jointly with a Japanese company WACOM, the latest neurocomputer version was developed and tested on image recognition tasks.
Subsequent departmental research was related to the development of neural network information technologies. Effective neural network classification systems were developed, used in texture recognition, voice-based identity verification, handwriting and connected word recognition and so on. Notwithstanding the applied nature of this research work, the Department preserved the skills instilled by N.M.Amosov: the global approach to problems within Artificial Intelligence, the ability to view the task as a whole and to accumulate experience for "breakthroughs" to come.