MOSCOW, October 3. A mathematical model of an “electronic nose”, based on the use of advanced biosimilar elemental base, was proposed by UNN scientists. According to them, the development will become the basis for devices that are much superior to existing analogues in recognition accuracy. The results were published in the journal Biomimetics.
The development of “electronic noses,” according to scientists, is very relevant today: such devices can be used in environmental supervision and the food industry, in security systems, in medicine for prosthetics or disease screening.
July 1, 08:00
The scientific race to find ways to imitate the human sense of smell, as experts noted, is now in full swing, since all existing electronic analogues or mathematical models have insufficient accuracy and a number of other limitations.
Scientists of the National Research Nizhny Novgorod State University named after N.I. Lobachevsky (Nizhny Novgorod State University) proposed a new approach to this problem, based on the use of memristors.
Memristors are a recently developed type of electronic element base that reproduces the work of biological synapses that transmit nerve impulses between brain neurons.
< br />1 of 3
2 of 3
3 of 3
1 of 3
2 of 3
3 of 3
“We have shown that using memristors and spiking neural networks, it is possible to build a universal and accurate analogue of the biological sense of smell, embodied “in hardware.” A regular chromatograph can serve as a sensor for such a “nose”, and to recognize a substance, a small concentration of odor will be enough for it,” said Sergei Stasenko, associate professor of the department of neurotechnology at the Institute of Biology and Biomedicine of UNN.
In the work of UNN specialists, a mathematical model of memristors was used, since mass production of memristor microchips has not yet begun, the scientists explained. According to them, the use of these elements will make it possible to develop a whole family of new electronic devices based on “brain-like” principles that have increased functionality relative to conventional electronics.
“In a fairly short term, our mathematical model can be implemented in the form of a miniature device, whose recognition abilities will not be limited to a predefined set of samples, like existing neural network analogues,” Stasenko emphasized.
At the moment According to scientists, there is almost no work using memristors in functional biological systems. The results obtained are of great importance for the development of neuroprocessors and neurocomputing in general, the authors believe.
“In our research, mathematical modeling of information processes in the brain and the development of mathematical models of memristors are extremely important aspects. Our research group has both expertise at the world level,” noted Stasenko.
In the future, the research team intends to prepare a new model for implementation in an electronic device, as well as continue research into the capabilities of memristors in systems that simulate brain function .