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 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.

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.

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.

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 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 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.