While deep learning models have achieved the state-of-the-art performance on single-image rain removal, most methods only consider fixed mapping rules single synthetic dataset for lifetime. This limits real-life application as iterative optimization may change and training samples. However, when learn a sequence of datasets in multiple incremental steps, they are susceptible to catastrophic for...

We describe a quantum algorithm for computing the intersection of two sets and its application to associative memory. The algorithm is based on a modification of Grover’s quantum search algorithm (Grover, 1996). We present algorithms for pattern retrieval, pattern completion, and pattern correction. We show that the quantum associative memory can store an exponential number of memories and retr...

s. The model of associative memory is proposed in this paper based on concept of association between images and associative search. This model may be used for connect concept of inference with associative processing in neural networks.