This document discusses biological neurons, artificial neurons, and cellular neural networks (CNNs). It provides an overview of CNNs, including their history, architecture, applications, advantages, and future scope. CNNs were proposed to reduce the number of interconnections between neurons in neural networks by only connecting neurons within a local neighborhood. A CNN is an array of dynamical systems with local connections only. Each cell in the CNN interacts with neighboring cells.

1. Biological Neurons Artificial Neurons

2. CELLULAR NEURAL NETWORKS G. Shruthi 06B61A0521 Under the Guidance of Rajashree sutrawe Assoc. Prof CSE-Dept & HOD of IT Dept

15. Figure: Experimental results in different noise conditions with CNN.

17. CONCLUSION CNN processors have been implemented using current technology and there are plans to implement CNN processors into future technologies. They include the necessary interfaces for programming and interfacing, and have been implemented in a variety of systems and provide value to their users. Researchers are also transitioning CNN processors into emerging technologies.

18. Future Scope One potential future application of CNN microprocessors is to combine them with the DNA microarrays to allow for a near- real time DNA analysis of hundreds of thousands of different DNA sequences.

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