The foundation of life phenomenon is the abilities of representation, memory and behavior of a life form. Human natural language can describe and interpret this matter world and naturally support the subjective initiative of humans. Not as a computer system, the brain neurons can realize complex interconnections with each other in 3D physical space, such as in which no word is stored repeatedly, and form the matter base of consciousness activity. It is known that the radial basis function representation principle is widely used to represent color, sound, smell and gustation, this paper tries to use a quantitative analysis method to reasonably estimate the number of single wavelength color attributes being represented by our brain. It is also known that some simple neurons in the primary cortex are sensitive to the direction of short line, this paper introduces the representation principle of single basis inclination which can represent the inclination attribute of a shorter line, and our brain can further extract more topology attributes of a shape through introducing the concept of vision event that is the evolution foundation of cognition ability. By the mechanisms of semantics lumpability and semantics abstract our brain can construct and represent more complex semantics. This paper emphasizes that both the semantics in natural language and the original semantics only perceived by our brain exist in the neural fiber plexus nodes of brain, they are twins. We humans always tries to consider this world as a whole, just as at a certain moment the neurons activated by the brain attention form an expanded semantics, while the shifting of attention forms a consciousness stream, so the semantics and syntax can be rationally expanded, which can be represented through the semantics abstract mechanism, specially it is our behavior with the subjective initiative making us distinguishing from animals to have shaped the consciousness stream structure. This paper also underpins the principle of matter primacy. We also explain why the brain consumes less power. In current technique stage, humans endowing a machine or a system with intelligence is feasible. That developing a kind of computer language which can analyze the attributes of semantics and semantics abstract in physical world can implement a Digital-Twin system, and through a great deal of practical training and simulation, we can help a machine to construct a semantics vector-base which contain much many semantics and semantics abstract with a hierarchy structure, which concern with all the behaviors that occurred. Therefore, based on the semantics vector-base and applying the real-time planning technique, we can construct an intelligence automation machine or system such as a humanoid robot and an AI agent.

In nature, the essence of intelligence phenomenon is the abilities of representation, memory and behavior of life form originated from the motion and interaction among a great number of microscopic matters. Using semantics in natural language can describe and interpret this physical world in various scenarios. Specially the brain neurons can link more effectively each other in 3D physical space than a computer, such as our brain doesn't save certain word in multiple places, then semantics is with the form of hierarchy structure, this also forms the matter base of consciousness activity. We emphasize semantics that can emerge and be expanded along with the time-axis exist in the neural fiber plexus nodes of brain. Therefore, following a special evolution stage of intelligence, through the reinforcement learning method based on the hierarchy structure and the time-sequence segments in semantics we can construct an intelligence automation system such as nuclear-powered submarine, and especially one humanoid robot can naturally embed into the semantics structural pattern. In addition, Appendix-A introduces my paper-the generation of semantics in natural language and the formation of brain, https://www.techrxiv.org, it gives us much deep understanding to the essence of semantics.

The human natural language is the operation system of our consciousness activity, and before it appeared we human interacted with the nature and each other typically through the image and sound, of course human beings also are the part of nature. The use of tools catalyzes the generation of natural language, in which the semantics space established in the image and sound of nature has been expanded greatly. The brain consciousness behavior depends on the attention mechanism which can extract the specified semantics, and this paper introduces the brain’s general stimulation-response mechanism that can decompose the semantics in natural language. Based on this kind of mechanism rather than computing-power and the current computer processing ability, it is sure that we are able to better simulate the brain intelligence.

We have known that in our eyes and ears, to the external stimulations there exist many cells that are respectively most sensitive to some specific center frequencies, and this paper has  discussed that the neuron system utilizes the transient response zone to represent different stimulation intensity levels, therefore we can generally use the Gaussian radial basis function model to explain that the neuron system is how to analyze the sound and color in the associated primary layer, and also can better explain some phenomena in the color cognitive behaviors. In addition, we have known that in the cerebral cortex, many small neuron groups are respectively sensitive to the different arrangement directions of line segments, and we find that the neuron system can further  extract the high-order information of a curve-line segment at the corresponding position, then as introduced later, the vison neuron system can conveniently represent a curve-line segment with an attribute-set constructed by using the polynomial radial basis function model related to the Taylor series expansion approach.

For a long-distance guard radar, MTI filter usually employs low staggered pulse repetition frequencies (PRF) modulation technique to overcome blind speed and detect the targets at low altitude in the presence of clutter. For a given ratio of the maximum-to-the minimum period, we find that there exists an optimum stagger ratios construction criterion (OSRCC) which can guarantee the first null depth minimum, and the associated estimation formula containing variable    has been derived successfully. In addition, based on more understanding to the properties of staggered PRF, we introduce a new stagger ratios optimization method that is much simple, efficient and flexible. In brief, this paper has thoroughly deconstructed this important basic technique in radar system.