Neural Information Organizing and Processing -- Neural Machines

In nature, neural information processing emerged with the necessity of complex beings such as animals to manage information in a more dynamic manner to ensure their interaction with an unpredictable environment, and implicitly their survival, by specialize certain cells for information management purpose through the nervous system as an integrative component of sensing and actuating (afferent and efferent) external and internal information by developing functions aimed to ensuring the adaptive and resilient characteristics. Through computing systems, the neural type of information processing began to be investigated for its perspective of use within artificial computing systems for understanding and validating natural neural processes through simulations as well for constructing devices with neural specific functions, consequently, various neural information aspects being highlighted over the time [1-17]. The neural information processing methods, although they have a tortuous history and do not have yet a coherent model not even at a fundamental level, are beginning to prove convincing in areas where specifically neural processes are more relevant than purely digital ones, such as: natural languages processing (text transformations, speech recognition and synthesis, etc.), patterns recognition, creative processing (multimedia), data analysis (healthcare, finance), control and coordination (robotics), etc. [7 - 17]. Since in essence the neural processes realize functional transformations of some contextual information, they are find usefulness in related fields such as formal systems, computing tools (compilers, libraries), etc. [18, 19].