Some of the pioneering advancements in neural networks research in the last decade have opened up a new frontier in machine learning that is generally called by the name deep learning (references 5 and 7 in the References section of this chapter). The general definition of deep learning is, a class of machine learning techniques, where many layers of information processing stages in hierarchical supervised architectures are exploited for unsupervised feature learning and for pattern analysis/classification. The essence of deep learning is to compute hierarchical features or representations of the observational data, where the higher-level features or factors are defined from lower-level ones (reference 8 in the References section of this chapter). Although there are many similar definitions and architectures for deep learning, two common elements in all of them are: multiple layers of nonlinear information processing and supervised or unsupervised learning...