To accelerate the learning of reinforcement learning, many types of function approximation are used to represent state value. However function approximation reduces the accuracy o...
In a previous paper [1], we have presented a new linear classification algorithm, Principal Component Null Space Analysis (PCNSA) which is designed for problems like object recogn...
The deconvolution of blurred and noisy satellite images is an ill-posed inverse problem, which can be regularized within a Bayesian context by using an a priori model of the recon...
Latent Semantic Indexing (LSI) has been validated to be effective on many small scale text collections. However, little evidence has shown its effectiveness on unsampled large sca...
— We study the problem of relay selection in a wireless cooperative network. Assuming a single source, a single destination, and N uniformly distributed candidate relays, we seek...