42 results about "Boolean network" patented technology

A Boolean Network rule engine is described. In one embodiment, for example, a system for evaluation of a set of rules based on input data is described that comprises: a rules interface for receiving a set of rules, each rule having at least one condition; a network builder for building a Boolean Network representation of the set of rules, the Boolean Network representation including transducers linked by logic gates, each transducer generating a Boolean value based on evaluating an item of input data against a condition of a rule; and a runtime evaluation engine for receiving input data, detecting changed items of input data, activating links among transducers and logic gates of the Boolean Network representation based on the changed items of input data so as to utilize transducers and logic gates of the Boolean Network representation relevant to rule evaluation outcome, and evaluating rules based on the input data and active transducers and logic gates of the Boolean Network representation.

The invention provides a true-random-number generator based on an autonomous boolean network structure. The generator is used to solve the technical problem of poor entropy source stability existing in existing true-random-number generators, and includes an oscillating circuit and a sampling circuit. The autonomous boolean network structure formed by N+1 logic gates is adopted for the oscillatingcircuit. One input port of one of the logic gates is connected with an output port of a right neighbor logic gate, another input port is connected with an output port of a logic gate after k left spacing logic gates, and the last input port is connected with an output port of the one of the logic gates through a time delay self-feedback circuit. The sampling circuit includes N+1 D flip-flops and an exclusive-or gate. Input ports of the flip-flops are connected with the output ports of the logic gates of the oscillating circuit. Input ports of the exclusive-or gate are connected with output ports of the flip-flops. An output port of the exclusive-or gate is used as an output port of the true-random-number generator. According to the generator, entropy source stability is not impacted by thenumber of nodes, and random-number output frequency can reach 300MHz. The generator is used in the field of secure communication.

A Boolean Network rule engine for evaluation of rules is described that comprises: a rules interface for receiving a set of rules, each rule having at least one condition; a network builder for building a Boolean Network representation of the set of rules including transducers linked by logic gates, each transducer generating a Boolean value based on evaluating an item of input data against a condition of a rule; and a runtime evaluation engine for receiving input data, detecting changed items of input data, activating links among transducers and logic gates of the Boolean Network representation based on the changed items of input data so as to utilize transducers and logic gates of the Boolean Network representation relevant to rule evaluation outcome, evaluating rules based on the input data and active transducers and logic gates and returning results of rule evaluation.

The invention discloses a high-speed random number generation method and apparatus. The apparatus comprises two parts including an entropy source module and an entropy sampling module. The entropy source module is an autonomous Boolean network consisting of digital logic gates; the network consists of an XNOR gate and N-1 XOR gates; N is equal to 3n (n is a positive integer); and the entropy source module can generate a chaotic signal with a wide and flat spectrum. The entropy sampling module is composed of a D trigger, and performs sampling and quantization on the chaotic signal to generate arandom number sequence. The generated random number sequence can pass random number industry test standards (NIST and Diehard statistical tests), and has good random statistical characteristic. The apparatus consists of the digital logic gates, and is simple in circuit structure and easy to integrate and manufacture; and a post-processing algorithm or circuit necessary for a conventional random number generation apparatus is not required, so that the power consumption can be greatly reduced. The high-speed random number generation method and apparatus can be widely applied to the field of information security of secret communication, key distribution, data encryption and the like.

The invention discloses a true random number generation method and device with a detection and correction function. A random number is taken as an important component of a cryptosystem and is widely applied to a security system. The random number comprises a session key, an initial vector and a digital signature. The device is composed of an entropy source module, a sampling module, an XOR logic gate, a cellular finite state machine, a test module, a CPU and a selection controller. The entropy source module is composed of two identical oscillator structures. Each oscillator is a chaotic oscillator structure based on an autonomous Boolean network. The entropy source module can generate wide spectrum and high bandwidth chaotic signals. After a random sequence is tested through the test module, whether the sequence passes the test or not is judged through the CPU. The sequence is directly output if the sequence passes the test. Data is returned and enters a postprocessing module through an XOR circuit if the sequence does not pass the test. Moreover, a selection controller selects different postprocessing modes to process the data. The processed data enters the test module for test again, until the data passes the test. A random code sequence generated by the invention can pass a random number industry standard test.

A method for setting up a knowledge map comprises the steps that propositions are used as nodes, implication operators used for showing logical relations between the propositions are linked with the nodes, a special Boolean network is formed, and the knowledge map is set up. The logical relations are the relations between logical connectors and Boolean functions, and the implication operators comprise binary implication operators, ternary implication operators and multivariate implication operators. The method extends the working method of a propositional logic, and develops an undirected acyclic graph knowledge expressive method having nothing to do with specific application scenes, and automatic reasoning of knowledge of the mathematics and sciences can be more conveniently achieved.

The invention relates to a true random number generator. The true random number generator comprises a hybrid Boolean network module, a function conversion module and a sampling processing module. Thehybrid Boolean network module comprises a plurality of Boolean units; the function conversion module is connected with an output end of a first exclusive-OR logic gate in the first Boolean unit and afirst input end of a first multiplexer; and the first input end of the sampling processing module is connected with the output end of the hybrid Boolean network module, and the second input end of thesampling processing module inputs clock signals. The true random number generator provided by the invention has a physical unclonable function structure with a true random number generation function,and can realize mutual conversion between a physical unclonable function function and a true random number generator function according to actual requirements.

The invention relates to an underwater robot posture adjusting and controlling device based on Boolean network, and a method. The device comprises a temperature sensor used for respectively collectingthe real-time temperature of seawater and a propulsion motor; a pressure sensor, used for monitoring the water depth and pressure of working points; an electronic compass, used for monitoring the heading and posture of a submersible vehicle; a sonar, used for detecting barriers and measuring the relative distance; a Boolean network control module, whose input node is respectively corresponding tothe temperature sensor, the pressure sensor, the electronic compass, and the sonar, and is used for receiving the collected data, and whose output node is corresponding to a motor driver, with its ouput state after coding being used for driving the propulsion motor; the propulsion motor, used for adjusting and controlling the posture of the underwater robot. Compared with the prior art, the invention is advantageous in that with the controlling means, the adjusting and controlling of automatic posture of the underwater robot can be realized; as the controlling method is based on the Boolean network model, logic is determined, network establishing is flexible, and control robustness is strong.

The invention provides a calculating method of restrictive boolean network degeneracy. The calculating method of the restrictive boolean network degeneracy comprises the following steps of carrying out set partitioning on all nodes in a transduction layer, grouping partitioned sets; in each group, calculating function contribution overlap amount, as shown in the figure, between each set and a complementary set thereof, and averaging to obtain a mean as shown in the figure; summing the function contribution overlap amount mean of each group, wherein the obtained result is the degeneracy of a restrictive boolean network. The calculation formula of the restrictive boolean network degeneracy is shown in the figure. According to the calculating method of the restrictive boolean network degeneracy provided by the invention, knowledge on biology degeneracy is step up to quantitative depiction from qualitative description, and a degeneracy phenomenon in a complex biological network can be cognized accurately and conveniently.

A method of creating logic chains in a Boolean network of a reconfigurable fabric is provided. The method includes creating a plurality of logic chains in the reconfigurable fabric. The plurality of logic chains include at least one arithmetic logic chain and at least one non-arithmetic logic chain. A method of creating logic chains in a Boolean network of a look-up table based FPGA includes: applying a labeling method by (a) finding a depth increasing node, (b) isolating the depth increasing node, and (c) finding minimum height cuts; mapping to generate a mapping solution using the minimum height cuts; applying a duplication method to implement an exclusivity constraint; and arranging connections in the look-up table based FPGA using the logic chains.

The invention discloses a dynamic fuzzy Boolean network control system and a building method thereof. On the basis of converting logical operation of the Boolean control network to algebraic operation by a matrix semi-tensor product theory, by using dynamic fuzzy model features, a local model and a global model for the dynamic fuzzy Boolean network control system are built respectively. Nonlinear fuzzy modeling can be realized for a nonlinear Boolean network system, and the control effects are good.

Logic Gate (100), particularly for integrated circuits including a Boolean network (105) having at least an input (106) and having at least an output node (107) and at least a terminal (108) connected to a first node at fixed potential (109) corresponding to a first logical level of the gate. The gate is characterized by the fact that the output node (107) is connected to a first pair of switches including a first switch (101) and a second switch (102), which are activated alternately, and are connected respectively, by a respective terminal, to the first node (109) at fixed potential and to the output node (107). Between the two switches there is a second pair of switches (103, 104) connected to a second node at fixed potential (110) corresponding to a second logical level of the gate. The switches of the second pair of switches are connected together in a way that the turning on of one switch of the second pair involves the turning off of the other switch of the second pair and the turning on of one of the switches of the second pair is suitable to bring the output node (107) to the potential of the second node at fixed potential (110).

The invention relates to a method and device for controlling a Boolean network robot. The method comprises the steps that a Boolean network model of the robot is constructed; a superposition method ora method of development is adopted for obtaining auxiliary matrixes corresponding to all nodes in the Boolean network model according to dynamic description in the Boolean network model; a node structure matrix is computed according to the obtained auxiliary matrixes; a network structure matrix is obtained through the correspondence between the network structure matrix and the node structure matrix; and the Boolean network robot is controlled according to the network structure matrix. By transforming the computational problem of the network structure matrix into a solution to the auxiliary matrixes with special structures and then transforming computation of the auxiliary matrixes into a simple matrix operation through the superposition method or the method of development, the computational complexity is lowered, the computation speed is increased, and the real-time requirements in robot control are met.

The embodiment of the invention discloses a method for simulating the tumor cell state through a Boolean network. The method comprises the steps that continuous expression spectrum data of a biological sample gene is acquired through a gene chip collecting technique, and an initial gene regulatory network is constructed according to the continuous expression spectrum data; deletion regulation is conducted on the initial gene regulatory network on the basis of the preset gene relevance to obtain a related gene regulatory network, and the related gene regulatory network is calculated through a Boolean function to obtain a single attractor of the related gene regulatory network; the regulatory range of a target gene in the initial gene regulatory network is determined and converted into an attractor of a compound Boolean function according to the single attractor of the related gene regulatory network, and then the converted attractor and a cell attractor are matched to determine the tumor cell state. According to the method, an overall understanding on the tumor gene can be achieved, tumors are quickly identified, and a powerful theoretical framework is provided for tumor treatment research.

The invention relates to a maximum grade predication method based on a binding Boolean network. The maximum grade predication method comprises the following steps that 1, relative mutual information is calculated to determine a candidate predicated gene set; 2, father genes used as target genes are selected from the predicated gene set obtained in the step 1 through the maximum grade predication method. The maximum grade predication method is suitable for predicating the relation of multiple variables based on small-sample data, has stronger robustness on noise, and is more suitable for predicating biological data under a real environment, the predicated network structure is more accurate and detailed, and the right number and the directivity of regulating and control relations and positive and negative regulating and control relations are predicated.

The invention discloses a predecessor unsatisfied attractor algorithm of a period control Boolean network. The predecessor unsatisfied attractor algorithm comprises the steps of calculating an obtained attractor state set through sampling, and then determining whether partial state of a Boolean control network is unstable according to the attractor state set; on the condition whether the partial state is stable cannot be determined through the attractor state set, determining whether the partial state in unstable through predecessor iterative calculation, thereby establishing a partial state database; according to a partial state database, constructing a relatively small scale network state set; and then performing transversal on the Boolean control network for obtaining all attractors. Through the attractor calculating method, the calculation amount in attractor calculation is greatly reduced, the algorithm can quickly process attractor calculation of a relatively large-scale large-average-period control Boolean control network. The algorithm improves further understanding of internal essential characteristic and property of the Boolean control network, and generates tool examination for designing a controller of the Boolean control network.

The invention discloses an apparatus and a method for simulating a single photon pulse signal source. The apparatus comprises a quartz crystal oscillator, at least three low-speed Poisson pulse generators and multi-input logic or gates. The method comprises the following steps: 1), generating a low-speed Poisson pulse signal; 2), generating and simulating the single photon pulse signal and other steps. Comparing with the prior art, the invention has the following beneficial effects: the apparatus of the invention is based on the reconfigurable property of the FPGA, the integration is high, thecomposition is simple, the cost is low, the total number of used logic gates is small, and requirements for a CPU is low; the single-photon pulse signal source is simulated based on a Boolean network, a Poisson distribution model is realized by utilizing characteristics of FPGA parallel processing, and the method of the invention has the advantages of being high in efficiency, convenient, high insignal-to-noise ratio, good in stability and low in cost, and the simulation degree of the single photon pulse signal source is close to ideal single photon pulse signal source under actual conditions.

As an important part of the cryptosystem, random numbers are widely used in security systems, such as session keys, initialization vectors and digital signatures. The invention is a method and device for generating true random numbers, which are composed of an entropy source module, a sampling module, an exclusive OR logic gate, a cell state machine, a test module, a CPU and a selection controller. The entropy source module is composed of two identical oscillator structures, which is a chaotic oscillator structure based on an autonomous Boolean network. The entropy source module can generate chaotic signals with wide frequency spectrum and high bandwidth. After the random sequence is tested by the test module, the CPU judges whether it passes the test, and if it passes, the sequence is directly output; if it fails, the data is returned to the post-processing module through the XOR circuit. At the same time, select the controller to select different post-processing methods to process the data, and after processing, enter the test module again for testing until the test is passed. The random code sequence generated by the present invention can pass the random number industry standard test.

The invention relates to a maximum score prediction method based on a constrained Boolean network, comprising the following steps: the first step is to calculate the relative mutual information to determine the candidate prediction gene set; the second step is to obtain the maximum score prediction method from the first step Select the parent gene as the target gene in the predicted gene set. The present invention is suitable for predicting the relationship between multiple variables based on small sample data. The present invention is more robust to noise and more suitable for biological For the prediction of data, the network structure of the invention prediction is more accurate and detailed, which is reflected in the correct number of predicted regulatory relationships, the directionality of regulatory relationships, and positive and negative regulatory relationships.

The invention provides an optimal control method for a gene regulation network. The optimal control method comprises the following steps: modeling a PBN (Probabilistic Boolean Network) with interference and context dependent in a probabilistic model detector PRISM to obtain a PRISM-based probabilistic Boolean network model; setting different state return values for a state of the PBN by using a reward structure in the PRISM, wherein the state return values are used for representing a control cost function and terminal cost; determining a first temporal logic formula and a second temporal logic formula respectively for control cost optimization for a limited range and an unlimited range; inputting the PRISM-based probabilistic Boolean network model, the different state return values, the first temporal logic formula and the second temporal logic formula into the probabilistic model detector PRISM to obtain the best optimal control result. The optimal control method, provided by the invention, for the gene regulation network can improve the efficiency for acquiring the best optimal control result under a condition of occupation of relatively low memory capacity.

The invention belongs to the technical field of integrated circuits, and particularly relates to a Gbps-magnitude high-speed real-time physical random number generation method and device, and the device comprises a physical entropy source module, an entropy extraction module, a post-processing circuit module and a gigabit transceiver module. The physical entropy source uses a 66-node autonomous Boolean network to generate a chaotic signal. A D trigger is used as an entropy extractor to extract the chaotic analog signal into a chaotic digital signal. The post-processing circuit is used for carrying out depolarization and decorrelation operation on the single-path chaotic digital signal, and finally the gigabit transceiver is used for carrying out serialization output to obtain a single-pathhigh-speed real-time physical random number. High-speed real-time physical random numbers can be generated in real time, integration and miniaturization of the high-speed physical random numbers areachieved, and the technical requirements of communication technology development are met.

A new type of general-purpose programming is disclosed. A new method and system models a computer program as the data flowing between computational nodes that perform operations where node connections are described by Boolean functions or logical expressions. Before or during program execution the initial Boolean network of nodes and logical connections is resolved into unambiguous directed execution graph. Boolean Multi-flow method is inherently parallel and can work well in large systems. Boolean Multi-Flow programs able to analyze diverse, heterogeneous and possibly conflicting set of inputs each requiring different topologies of the underlying computational graph.

The invention provides a true-random-number generator based on an autonomous boolean network structure. The generator is used to solve the technical problem of poor entropy source stability existing in existing true-random-number generators, and includes an oscillating circuit and a sampling circuit. The autonomous boolean network structure formed by N+1 logic gates is adopted for the oscillatingcircuit. One input port of one of the logic gates is connected with an output port of a right neighbor logic gate, another input port is connected with an output port of a logic gate after k left spacing logic gates, and the last input port is connected with an output port of the one of the logic gates through a time delay self-feedback circuit. The sampling circuit includes N+1 D flip-flops and an exclusive-or gate. Input ports of the flip-flops are connected with the output ports of the logic gates of the oscillating circuit. Input ports of the exclusive-or gate are connected with output ports of the flip-flops. An output port of the exclusive-or gate is used as an output port of the true-random-number generator. According to the generator, entropy source stability is not impacted by thenumber of nodes, and random-number output frequency can reach 300MHz. The generator is used in the field of secure communication.

The invention relates to a method and device for controlling a Boolean network robot. The method comprises the steps that a Boolean network model of the robot is constructed; a superposition method ora method of development is adopted for obtaining auxiliary matrixes corresponding to all nodes in the Boolean network model according to dynamic description in the Boolean network model; a node structure matrix is computed according to the obtained auxiliary matrixes; a network structure matrix is obtained through the correspondence between the network structure matrix and the node structure matrix; and the Boolean network robot is controlled according to the network structure matrix. By transforming the computational problem of the network structure matrix into a solution to the auxiliary matrixes with special structures and then transforming computation of the auxiliary matrixes into a simple matrix operation through the superposition method or the method of development, the computational complexity is lowered, the computation speed is increased, and the real-time requirements in robot control are met.

The present invention relates to a Boolean network-based attitude adjustment control device and method for an underwater robot. The device includes: a temperature sensor for collecting the real-time temperatures of seawater and a propulsion motor; a pressure sensor for monitoring the water depth of the working point and pressure; electronic compass, used to monitor the heading and attitude of the submersible; sonar, used to detect obstacles and measure relative distance; Boolean network control module, the input nodes correspond to temperature sensor, pressure sensor, electronic compass and sonar respectively, It is used to receive the collected data, the output node corresponds to the motor driver, and its output state is encoded to drive the propulsion motor; the propulsion motor is used to realize the attitude adjustment control of the underwater robot. Compared with the prior art, the control device proposed by the present invention realizes the autonomous attitude adjustment control of the underwater robot, and the proposed control method is based on a Boolean network model, which has the advantages of logical determination, flexible network construction, and strong control robustness.

The invention discloses an apparatus and a method for simulating a single photon pulse signal source. The apparatus comprises a quartz crystal oscillator, at least three low-speed Poisson pulse generators and multi-input logic or gates. The method comprises the following steps: 1), generating a low-speed Poisson pulse signal; 2), generating and simulating the single photon pulse signal and other steps. Comparing with the prior art, the invention has the following beneficial effects: the apparatus of the invention is based on the reconfigurable property of the FPGA, the integration is high, thecomposition is simple, the cost is low, the total number of used logic gates is small, and requirements for a CPU is low; the single-photon pulse signal source is simulated based on a Boolean network, a Poisson distribution model is realized by utilizing characteristics of FPGA parallel processing, and the method of the invention has the advantages of being high in efficiency, convenient, high insignal-to-noise ratio, good in stability and low in cost, and the simulation degree of the single photon pulse signal source is close to ideal single photon pulse signal source under actual conditions.

The invention discloses an entropy source based on asynchronous feedback units and a feedback coefficient calculation method, the entropy source comprises a plurality of asynchronous feedback units, the hardware overhead and jitter feedback delay are greatly reduced under the condition of ensuring the output randomness of the entropy source, and the asynchronous feedback units can become entropy source general structure units. Connection between the asynchronous feedback units is controlled by feedback coefficients, a corresponding random Boolean network model is provided as guidance of coefficient selection, optimal feedback coefficient configuration is selected according to whether a Boolean network tends to chaos or not, and coefficient selection can be more reliably and conveniently transplanted to a pure digital logic hardware implementation platform.

The invention relates to a true random number generator. The true random number generator comprises: a mixed Boolean network module, a function conversion module and a sampling processing module; the mixed Boolean network module comprises a plurality of Boolean units; the function conversion module is connected with the first Boolean unit respectively The output end of an XOR logic gate is connected with the first input end of the first first multiplexer; the first input end of the sampling processing module is connected with the output end of the mixed Boolean network module, and the A clock signal is input to the second input terminal of the sampling processing module. A true random number generator provided by the present invention has a physical unclonable function structure with a true random number generating function, and can realize mutual conversion between a physical unclonable function function and a true random number generator function according to actual needs.