Reasoning by SVD and morphotronic network

The immune system of the vertebrates possess the capabilities of "intelligent" information processing, which include memory, the ability to learn, to recognize, and to make decisions with respect to unknown situations. The mathematical formalization of these capabilities forms the basis of immune-computing (IC) as a new computing approach that replicates the principles of information processing by proteins and immune networks. This IC approach looks rather constructive as a basis for a new kind of computing. With the Morphotronic System or the analogous SVD we can create effective learning process and create immune memory by the projection operators. Given the immune memory is possible to recognize and compare antigen in a way to take defense action to eliminate the dangerous cell

Morphotronic system (theory)

The Morphotronic approach postulates a significant improvement to traditional system design thinking based on the Turing Machine model. The paper presents a range of important concepts and definitions supporting this proposition. The Morphotronic system represents an abstract universe of the objects. This universe of objects has two interpretations as in the case of the voltages and currents in the electrical circuit. For the space of the voltages the objects are the voltages at edges of the electrical circuit. For the current space of the currents the objects are the currents in any edge. The dimension of the object space is equal to the number of edges in the electrical circuit. Such a space allows dual interpretation of the current and voltages. Other possible dual variables can be used in the morphotronic system as forces and the fluxes in mechanics or dissipative thermodynamics, in a general way the dual interpretation of the object space will be denoted as causes and effects. The morphogenetic system can be modelled by samples of the causes and effects. The morphotronic system with the samples generates the algorithm to implement the purpose in the system. Providing that the samples of the effect and the purpose denote a virtual cause, the vector E can be computed so that it represents the effective origin of the causes inside the purpose map. With the cause-effect rule the effective causes can be computed obtaining results that are coherent with the samples. Providing that the virtual cause is given by purpose the effective causes can be generated in agreement with the samples. The described algorithm is denoted as the projection operator that transforms a virtual cause (purpose) into an effective cause. © 2009 Springer-Verlag Berlin Heidelberg

Morphotronics and Bond Graphs Representation

Bond Graphs theory can assist in tracking power movements in a system that is defined by effort and flow variables. An electronic circuit uses the network where flow (current) moves when affected by the effort (voltage). Morphotronics uses multidimensional vector space and transformations in this space to model bond graphs and the electronic circuit. Specifically, the flow (current) vector space or the effort (voltage) vector space is applied. In Morphotronics, an electronic circuit is a vector transformation operator in the space of voltage or current. Morphotronics offers a unique computational apparatus to create bond graphs and compute the power which moves through the graph. At the same time, Bond Graphs assist to visualise how the distance changes in the morphotronic system