This book provides insights into developing better algorithms for machine learning, artificial intelligence and signal processing.  The authors build mainly on two topics: Cognitive Dynamic Systems (CDS), which is a well-established paradigm originated in the Cognitive Systems Lab of McMaster University, and attention, an essential cognitive function the neurobiological root of which is assumed to be the reentry of neuronal firings through feedback connections. This book focuses completely on the perceptual part of a CDS, or in short, the “perceptor”, which is the part responsible for visualizing the environment. In this regard, inspired by the mammalian brain, an important step has been taken to redesign the perceptor and therefore improve its functionality in light of “attention”, a function that is essential to cognition. The authors demonstrate how the end result is an improved performance for the perceptor in the face of uncertainties and better separation of relevant information from irrelevant information.