Mathematical Logic, Operations at the Quantum Level - Formal Logic Symbolization (Language)

Speech recognition reveals that we can use deep learning to approximate the knowledge network structure of experts using big data (a combination of intrinsics)

Artificial intelligence, a systematic connection construction based on knowledge, with short search paths and a high degree of matching, actually mimics the natural selection of species construction processes in nature, and according to the median value theorem, there will always be an optimal value for our needs

The explosive growth of the combination can be constrained by combining breadth and depth - rapid convergence based on experience (proximity of eigenpaths, construction of fuzzy logic)

The explosive growth of data allows us to find different levels of intrinses and build them into certain patterns

The interconnection of all things makes the Internet thinking established, and the coupling of different dimensions makes professional knowledge universally acceptable, but a certain medium is required, such as Zhihu, and the user is also a part of the system

Database matching--- construction of neural networks (inference machines), --- construction of knowledge bases (can be interpreted through empirical inputs, outputs)

According to certain modules (title, abstract, method, introduction, conclusion), the depth of the intrinsic solution at different levels of the network is the selective expression of probability, the expression of a certain pattern, the existence of milestones is the key node, and the research is the intrinsic path connection that we derive based on previous experience

The intrinsic nature of the network serves as an observable indicator, just like the Turing test

The eigengenis is an approximation, and through the determination of the boundary, the probability of the Bayesian network can be solved to limit the explosive growth of the combination

The explosive growth of combinations requires certain eigens to constrain them, logic is a reliable method of linking existing knowledge, and distributions are higher-order existences, just as calculus is the study of variable forces

Big Background-Small Background-Problem Formulation (Mathematical Language Description, Existing Model Selection, Purpose Determination)-Method Selection-Effect Achievement: The Nature of Selective Expression, the Nature of the Network

The network of the whole discipline is the reverse solution of various intrinses

The basic unit of language, the domain. Pen ~ Fun ~ Pavilion www.biquge.info the continuous traversal of the levels to ascend the dimension, the similarity between the levels / modularity resulting in statistical network operations

Rules are knowledge, and the order between rules is determined by the degree of matching

Modeling language: deep learning, you have to have a certain amount of big data, and then you can talk about path optimization

The combination and dynamic change of feature points, and its certain convergence boundary is a certain pattern

The multi-level differentiation 101010111001 of concrete objects is inefficient, which is the intrinsic of the dendrogram, the convergence of different levels

Neural networks emphasize hierarchical structure, and the intrinsic interior of different levels is a network, and the connections between levels are also networks

Perception-understanding-decision-making, and the formation of reflection arcs are the characteristics of the network, but each level can be mapped to a secondary network, and there can be a feedback adjustment mechanism, so that it can learn and improve

A new language: neural networks

Expert system generation tools and auxiliary tools: LISP, PROLOG

Multi-logical network-based correspondence to construct the expression of probabilities

The questionnaire is like the input and selective output of the expert system (relying on combinations), in the form of a questionnaire (single choice, multiple choice, numeric, true or false), forming the structure of the network, which can be regarded as intrinsic when the network of the matrix is physically close to reality

Combination is the premise of the proliferation of knowledge networks

The path of the network is optimal for multiple hits, and the matrix scoring path is the result of local matching

Problem Determination—Knowledge Acquisition—Model Building—Implementation Phase (Programming: Knowledge Formalization, Knowledge Matching in Database; Algorithm Implementation)--System Testing, Improvement, and Learning (Refer to Zhihu, Wikipedia, User Maintenance)

The organization of knowledge, I tend to the list of databases, and then form new knowledge according to different degrees of matching, and the real knowledge is expressed selectively, that is, using probability weighting

Logical connections between modules

Fulfillment is king

Hidden Markov model probability changes, find a set of more reasonable probability matrices, i.e., eigens

Imitation of the physical picture, such as the lowest energy

The OEC system, centered on the hierarchy of objects, is both knowledge and work area (coupling): domain, class, tree, string

Essentially building complex systems: the differentiation of nodes (central node vs. general node) and distribution (the formation of small groups), power law, the tendency and probabilistic expression of the central node of the relationship connection of the new nodes (the tendency to connect the highly connected region, but the resources are limited and can only be allocated to the next level); the intrinsic of the network is the path, and its average path length (separated by six degrees) can be used as the surface division of the convergence radius; the degree of aggregation is an index of the hierarchy; the relative independence of the hierarchy, the formation of the model; the dynamic change of the network, the existence of the critical, the mathematical topology (the change of the probability of node distribution); the similarity of the hierarchy, the formation of oscillations and resonances; the statistical characteristics; the expression of nonlinear differential equations, the eigengens are also networksDynamics describes the movement of individuals, and the whole is described by statistical distribution, selective expression of natural selection, explosive growth of combinations brought about by hierarchical coupling, and the characteristic path of screening and convergence, basic units are the basic rules, and actual substances are units of various levels, and games of various levels of levels

The fundamental role, as revealed by Maxwell's equations, is the coupling relationship that I admire, symmetrical, and has a relationship of mutual transformation: the divergence indicates the closure of the line of force, the curl indicates that it is a different partial derivative of the high-dimensional structure (lifetime two), and the dynamic interroots are mutual, resisting the oscillation of change

It has a macroscopic property: the Holkieffer current/voltage law for circuits

The relationship connection of database and data can sort out a certain path, and take the loop as a basic unit, which can be input to a certain amount of output to produce a certain output

The relative independence of the data, the correlation is related to the similarity

Data management classifies, organizes, encodes, enters, stores, retrieves, maintains, and outputs data

mode

Data collection and automatic matching processing, certain organizational data structures

Establish sequence-oriented conceptual connections of data, where attributes do not need to be defined, only integrated

The result of the taxation of both sides will fluctuate to equilibrium in a certain time period, but time is a difference that can be profitable

Price discrimination is essentially stratification. Granularity

(Networking, Image Recognition, Biological Evolution, Probability Collapse, Linear Algebra)

Systems biology needs to think at the level of images, which is related to image recognition and computer algorithms. Complex interaction networks can be decomposed into matrices at different levels, so the solution of eigenvalues is crucial

Eigenvalues, multi-level intrinsics, including intrinsic intrinsics

The action is essentially a transformation, i.e. the transformation of a high-dimensional structure at different levels, based on a coordinate system (which has a relative and orthogonal axis)

The role of the matrix is statistically related, i.e. it can be used as a simulation. As a coupling, statistics can form matrix operations that reflect a distribution

The distribution of the network naturally creates distribution, and then there are hierarchical and hierarchical games, followed by the formation of potential differences, and the whole as a low-entropy body maintains a steady state (growth and evolution) through exchange with the outside world

Multi-level: average vector, eigenvector covariance matrix, different levels are iterated with Bayesian formulas. Face recognition is the matching and statistics of feature vectors

The eigenvectors of real symmetry matrices are constants and are related to conservation

The sum of the terms of the function of the coefficients, i.e., a matrix operation

Physiology is coupled with differential equations, which is a language of expression

Thermal change is coupled with electrical change

The presence of specific antigens on the surface of the red blood cell membrane and specific antibodies on the serum is a wonderful coupling, which is the result of distribution

The relationship between respiration and the circulatory system is complex, not only the effect of oxygen and the partial pressure of carbon dioxide on respiration (high partial pressure of oxygen and less breathing), but also the effect of blood pressure and respiration (high blood pressure and less breathing), which reflects a conservation relationship, but this is a macroscopic observation. It is deeply refined, and is related to the brain regulation and nervous system regulation of the body. (The medulla oblongata is the center that regulates respiratory movements.)

Breathing-heartbeat coupling is due to the proximity of the medullary respiratory center to the center that manages heartbeat and blood pressure (coupling of physical locations) and, more importantly, the neural connection between the centers

Biochemistry: the emergence of ensembles and overall patterns of multiple chemical reactions (due to the exponential and selective expression of combinations), the selective expression of networks, the treatment of probability by probabilistic networks, the nature of matrices through chemical reactions.

There are also different levels of dynamic equilibrium in the body, and we can understand a biochemical reaction process through differential equations formed by long-term changes

Hormones are regulated at a higher level, such as the hypothalamus, pituitary gland and other endocrine sites are important intrinsic features.

Acting similarly or opposite is a coupling of action, similar to an atom

The quantum level is like the difference in ion concentration caused by the opening and closing of sodium ion channels, that is, the change in electric current

Physiology: Rhythmic impulses are an intrinsic feature that is the homeostatic maintenance of the system. Coupling with muscles is the rhythmic movement of the body, such as breathing movements, the beating of the heart (non-conscious control). Multi-level perception with reflex as the basic unit: peripheral receptors (blood pressure and chemical concentration)

The carotid sinuses have nerve endings that sense changes in blood pressure (coupling nerves to blood vessels), and the signaling generated by the stimulation of elevated blood pressure can produce the ultimate feedback, that is, the cardiovascular center sends a signal to lower blood pressure (high-dimensional feedback regulation, maintaining homeostasis)

The carotid and aortic bodies are chemoreceptors, and changes in chemical composition can affect the transmission of signals and ultimately the center

Cross-perfusion enables the separation of the effects of blood pressure and CO2 concentration, and cross-connection of the carotid artery and jugular vein in different individuals

Multiple buffering mechanisms: blood pressure and respiratory coupling, chemical composition concentration changes, and respiratory coupling, all innervated by nerves, is an interesting example of network coupling

The generalized function of Laplace's change makes the discrete continuous, and the dimensions change

Rhythm is an orderly combination of combinations

Search is a match

Literature research is the coupling of multiple probabilistic networks, which enables the emergence of new ideas. For example, citation network is a multi-scale operation that relies on the matching of different granularities of the database

The probability of empirical changes, which are high-dimensional constructs, such as the power law and the Matthew effect, tend to favor nodes with high connectivity

The connection of different nodes is multidimensional

Logic is a way for nodes to form relationships

The ascending dimension of mathematics is the relationship between the levels of the network

The ultimate choice for large-scale combinations

A system is a complex of elements that interact with each other. This definition emphasizes the interaction between elements and the integration of elements by the system.

1. A system is a dynamic and complex whole, interacting structural and functional units.

2. The system is composed of different elements of energy, matter, and information flow.

3. Systems tend to be made up of entities that seek equilibrium and exhibit oscillating, chaotic, or exponential behavior.

4. A holistic system is the temporary interactive part of any interdependent set or group, and the 'parts' are made up of the system itself and other parts, which in turn are parts or "sub-wholes" that make up other systems.

The subhierarchical structure of the network is relatively independent, and its combined form is a kind of traversal, which makes the dimension change (ascending, like the original function). These combinations are a synthesis between elements at a larger level and can exhibit cyclical behavior, such as oscillations. The regulation between layers is like the role of a physical network

Relationships are dynamic and originative

The continuous inclusion of hierarchies and the selective expression of ---- networks that may eventually couple are the prerequisites for the emergence of hierarchies

The level of arithmetic 1011101, which is qualitative to quantitative. It's essentially probability, information entropy. As a measure of information, it depends on the context as the environment

Adaptability is the formation of new combinations

The coupling of reductionism and holism is the probabilistic network

The coupling of the combined network properties is a dynamic process, with the emergence of a holistic nature at sufficient spatiotemporal scales, and at the same time there are multiple feedback mechanisms in this process, which is the result of the hierarchical game, which is the tendency of energy minimization and entropy increase.

Emergence, which is the accumulation of probabilities to a certain threshold, is the structure of the network, which is a multilinear structure, i.e., nonlinear, matrix

The choice of environment is networked

effectiveness

The relativity of the system structure, the mutual transformation of dynamic and static, is understood holistically using the concept of wave function. Boundaries and other elements are modules of selective expression, which is the role of the feedback mechanism, and at the same time it is also varied, according to the relative relationship

Symmetry is an important property, find a group of points to describe its symmetry

The ultimate eigen, of the conflict of multiple forces of the network, is the mean of the distribution

When the scale of the hierarchy goes down to the quantum, it is necessary to consider the relativistic effect. Discrete and continuous are fractal dimensional structures, which are similarities between levels

The structure of a protein is like the choice of pathway

The feedback system, the differential equation, is linearized near the equilibrium point to obtain an algebraic characteristic equation, and the root of the equation is used as the basis for judging stability. The Laws-Hurwitz criterion is an algebraic basis for judging the position of the eigenroot in the s-plane according to the characteristic equation of the system, so as to determine the stability of the system

Logic, like hierarchy, is the expression of the network

From cause to effect, it is the result of the continuous formation of combinations

Turing machine programs can be executed on a finite network of neurons to build a neural network model.

Imagination is a selective representation of a network of reality, a high-dimensional structure

Acupuncture points are the essence of the network, and the combination of acupuncture points is also the essence of the network

Tender points are a series of biological network changes, as in neuro-humoral regulation: vascular radius (smooth muscle, also associated with factors such as hormones), hormones, various opposite effects, network autoregulation

;