90 results about "Logistic function" patented technology

A system and method of modeling a circulatory system including a regulatory mechanism parameter. In one embodiment, a regulatory mechanism parameter in a lumped parameter model is represented as a logistic function. In another embodiment, the circulatory system model includes a compliant vessel, the model having a parameter representing a change in pressure due to contraction of smooth muscles of a wall of the vessel.

The invention discloses a pedestrian identification method under a road traffic environment based on improved YOLOv3. The method comprises the following steps of: S1, acquiring and pre-processing an image, and making a pedestrian sample set; 2, calculating the length-width ratio of the pedestrian candidate frames by using a clustering algorithm and the training set; 3, inputting the training set into the YOLOv3 network for multi-task training and saving the trained weight file; S4, inputting a picture to be recognized into the YOLOv3 network to obtain a multi-scale characteristic map; S5, using a logistic function to activate the x, y, confidence degree and category probability of the network prediction, and obtaining the coordinates, confidence degree and category probability of all prediction frames by judging the threshold value; S6, generating a final target detection frame and a recognition result by carrying out the non-maximum value suppression processing on the above result. The method of the invention solves the problem of low detection accuracy of the prior method, realizes the multi-task training, does not need additional storage space, and is high in detection accuracyand fast in speed.

The embodiments herein relate to multi pattern searching and, more particularly, to multi pattern search or multi pattern matching using logic content processing. The input pattern is type cast to a Boolean alphabet and is then processed to create a corresponding signature set. Further, the signature set is divided into subsets and a Boolean logic function representing each signature subset is created. Further, the values of each subset are simultaneously compared with windows of an input data steam or data file to find a match. If a match is found, the system returns a hit, else a miss. Parallel stages may be added to enhance performance of the system, as multiple inputs may be processed at a time.

The invention discloses a P300 signal detection method based on an LSTM network. The method comprises the following steps: step one, an experiment is carried out by using a P300 character speller andEEG signals are extracted to form a training set and a testing set; step two, preprocessing is carried out on the collected data and the processed data are used as an input data set of a model; step three, an LSTM layer is designed as a spatio-temporal filter of the EEG data set, an all-connection layer is added after a least time step of the LSTM layer, a Softmax layer is added to convert a network output value into a probability form, and then the network is trained and a model parameter is determined, wherein the Softmax layer is a generalized form of the logic function; and step four, a model evaluation index and a testing set character recognition rate are calculate to verify the performance of the model. The method has the following characteristics: no manual feature extraction is needed; the recognition performance is good; the generalization ability is high; and the good information conversion rate is realized. The P300 signal detection method is a good P300 classification algorithm.

A logic simulation processor uses multi-state logic (e.g., in 4-state, signals may take the values 0, 1, X or Z in the simulation of a semiconductor chip design). Typically a reduced number of basic multi-state logic functions are selected for the instruction set of the processor. Logic functions that are not part of the basic set are simulated by constructing them from combinations of the basic logic functions. In this way, the instruction length remains a manageable size but all logic functions that may occur can be simulated. The basic VLIW architecture can be extended to other applications.

According to one embodiment of the present invention, a method and system for VLSI hardware design and synthesis is provided in which components provided by a heterogeneous modeling framework are interconnected, based on design specifications of a VLSI, to create a corresponding behavioral VLSI model. The heterogeneous modeling framework contains a first component library including logic functions that can be used to build hardware structural models and a second component library including numeric standard. The created model is simulated, tested, and functionally verified using discrete event domain simulation capabilities provided by the heterogeneous framework. A corresponding structural model is extracted from the tested behavioral VLSI model using a software tool provided by the heterogeneous modeling framework.

The invention discloses a pedestrian re-identification model, method and system for adaptive difficulty mining. The identification method comprises the steps of: randomly dividing sample pictures intoa training set used for each iteration, inputting the training set into a convolutional neural network, obtaining the probability that each sample pair belongs to a positive or negative sample pair by using a softmax function, and then obtaining the loss of each sample pair by using a multinomial logistic function; obtaining a difficult sample pair by using the loss of each sample pair; and training the convolutional neural network by using the difficult sample pair until the current number of iterations reaches the upper limit of the number of iterations, thus obtaining the pedestrian re-identification model. The pedestrian re-identification model is used to extract features of each picture in a picture set to be identified, and then a similarity order of the sample pairs in the pictureset to be identified is obtained. The pedestrian re-identification model, method and system avoid over-fitting and under-fitting, and have high recognition accuracy.

A method for improving performance tuning speed of a distributed system belongs to the technical category of performance optimization of a distributed computer system. The method is characterized by comprising the steps of quantizing the parameters with respective numeric area as a uniform parameter set in the distributed system including a web page server, an application programme server and a database server and composed of three-layer servers, obtaining the parameter set through uniform sampling, training by using a three-layer neural network model which comprises two hidden layers and of which each node is a logistic function, then repeatedly sampling, testing new parameters in the neural network to obtain rough response time and rough throughput rate, determining the sequencing performance curve and noise grade of the neural network based on the requirements of the system performance optimization, and finally obtaining the parameters of a regression function according to the set relative performance requirements so as to obtain the desired optimal parametric solution. The invention has the advantages that the invention improves the system performance and synchronously reduces test time.

Network logistics and network business are mutually integrated. In order to realize the sharing of logistics information and logistics functions among logistics enterprises, industrial and commercialenterprises and logistics supervision government departments, the network logistics has to be interconnected, intercommunicated and interoperated with network government affairs. The problem of logistics information comprehensive integration among logistics enterprises, industrial and commercial enterprises, financial institutions and government supervision departments in logistics can be effectively solved by means of the government affairs. Network logistics systems are closely related to the network business, the network government affairs, network intelligent traffic systems and the like.The network logistics is based on the network business, the network government affairs, the network intelligent traffic systems and the like. A plurality of identification facilities and a general purpose calculator are mutually connected in a short distance through transmission media according to physical topological structures of a local area network (in a star shape, a ring shape, a tree shapeor a bus shape and the like) to form a logistics network unit. Each identification facility is fixedly distributed in a monitoring area and respectively takes an identification task of cargoes and thelike of the monitoring area in the logistics system.

The invention discloses an urban trunk road travel time estimation method based on variable weight mixed distribution, and belongs to the technical field of intelligent traffic. The method comprises the steps: collecting a trunk road travel time parameter of a trunk road in a target research region, preprocessing and verifying the distribution mode of the trunk road travel time in all time periods, building a Gaussian mixed distribution model with a fixed weight, and determining an optimal component number K; collecting the flow in all flowing direction and a signal control parameter for an intersection and an road segment, and building a mixed distribution weight coefficient Logistic function with K components; building a variable weight mixed distribution model, estimating an unknown parameter in the variable weight mixed distribution model, and finally carrying out the estimation of trunk road travel time distribution and the estimation of reliability service level. Compared with a conventional single-distribution-function and fixed weight mixed distribution model, the method irons out the defects that the transplantability and the adaptability are poor, and can achieve the more accurate estimation and reliability evaluation of the trunk road travel time distribution.

The invention discloses a fixed polarity conversion method for design of a digital circuit. The method comprises the following steps of: firstly reading in an SOP (Sum-of-Products) expansion of a Boolean logic function containing irrelative items; respectively establishing a minterm index table and an irrelative item index table by utilizing a quick list technology; and finally, searching the optimal irrelative item for choice, selecting an appropriate irrelative item to be read in an FPRM (Fixed Polarity Reed Muller) functional expression to obtain an FPRM expansion with lest and items. The method has the advantages that the conversion of fixed polarity from the SOP expansion of the Boolean logic function containing the irrelative items to an RM expansion in the design process of the digital circuit is realized; through the test of ten 10 MCNC (microelectronics center of north carolina) Benchmark circuits, the result shows that: compared with the fixed polarity conversion method which does not consider the irrelative items, the method has the advantages that the FPRM expansion can be effectively simplified, and the RM logic circuit with smaller area, lower power consumption and faster speed is obtained.

The invention discloses a contact network failure risk assessment method based on a binary decision graph algorithm, comprising the steps of: (1) generating a BDD structure, determining system boundaries, basic events and top events, establishing and normalizing a fault tree, and generating a BDD structure, wherein the corresponding BDD nodes may be directly created by ITE operations for basic events; and ITE operations may be performed on basic events or other intermediate events to obtain the BDD structure of the original intermediate event for intermediate events; (2) calculating the accident rate of the contact network failure risk, generating a Boolean logic expression by the fault tree, and generating a Boolean logic function corresponding to the fault tree top event, wherein when the true value is obtained, the probability of occurrence of the top event or any intermediate event may be obtained; and (3) measuring the event importance. The invention applies the BDD method to thefailure risk assessment of the contact network, which simplifies the calculation process, and solves the problems such as the combined explosion and the complicated solving process encountered by thecut set method in the contact network failure fault tree analysis.

The invention discloses a pedestrian re-identification method based on a triple convolutional neural network. The method comprises the steps of 1, forming a small batch of samples; 2, outputting global features and local features of each pedestrian image; 3, calculating the distance between the global features of every two pedestrian images in the small-batch samples and the distance between the local features of the corresponding body parts; 4, forming P x K pairs of triple samples; 5, using a Log-logistic function to replace a hinge function to improve a triple convolutional neural network loss function; 6, obtaining a trained triple convolutional neural network; asnd step 7, identifying the target pedestrian image by using the trained triple convolutional neural network, and further avoiding mismatching between the target pedestrian image and the pedestrian image to be identified by combining a confidence measurement mechanism. According to the pedestrian re-identification method based on the triple convolutional neural network, pedestrian re-identification can be accurately carried out, and mismatching between different pedestrians is avoided.

A method and system for testing a circuit design. The method including generating a simulation model of the circuit design, the circuit design comprising one or more source latches, one or more destination latches and a logic function connected between the source latches and the destination latches; generating a modified simulation model of the simulation model by inserting random skew between an output of each source latch and an input of the logic function only in asynchronous data paths between the source latches and the destination latches of the simulation model; and running the modified simulation model.

The invention discloses a seismic source positioning method based on P-wave arrival time and waveform amplitude. The method comprises following steps of step 1, acquiring seismic source parameters through a micro-seismic monitoring system; step 2, in case of unknown P-wave wave speed v, solving a primary seismic source coordinate (x0, y0, z0) and corresponding speed v; step 3, calculating the slope K of a waveform amplitude trend line, wherein K is defined in the description; step 4, using the logistic function to fit the function relation expression between the slope K of the waveform amplitude trend line and the P-wave wave speed v of each seismic source; step 5, calculating the P-wave wave speed v<c> of each corrected sensor; and step 6, using the P-wave wave speed v<c> of each corrected sensor to solve a secondary seismic source coordinate (x, y, z). The method is characterized by high adaptability and precision.