Associative memories for chemical sensing

We consider application of neural associative memories to chemical image recognition. Chemical image recognition is identification of substance using chemical sensors' data. The primary advantage of associative memories as compared with feed-forward neural networks is high-speed learning. We have made experiments on odour recognition using hetero-associative and modular auto-associative memories. We have also tested backpropagation NNs with one hidden layer. Associative memories displayed recognition quality not worse than backpropagation networks.