158 results about "Finite state" patented technology

An exemplary system and method that generate a finite state automaton of a controller for sequential decision-making of a computing device for a user-requested task, the generation using automaton-based representations derived from outputs of a large-scale generative language model. The exemplary system and method receive a user command and (i) construct the finite state automaton by parsing GLM responses to prompts / queries for candidate steps and sub-steps for the task, and (ii) verify the finite state automaton, e.g., for logical errors, safety specification, performance specification, and intent of the user, and / or update the finite state automaton to meet such specifications. The state machine can be synthesized on the fly for real-time operation via the GLM outputs and evaluated in the same pipeline operation against physical models, safety models, etc., that can be combined to iteratively modify the state machine until it meets the verification requirements.

Described herein are technologies related to tokenizing alphanumeric text through use of a tokenization algorithm that is at least partially implemented as a finite state machine. The tokenization algorithm is configured to output numeric identifiers that represent tokens or sub-tokens in the alphanumeric text.

Embodiments disclosed herein include apparatuses for improved testing between chips. In an embodiment, an apparatus comprises a plurality of transmit clusters on a first chip, where individual ones of the plurality of transmit clusters comprise a set of transmit lanes on the first chip. In an embodiment, a plurality of finite state machines (FSMs) are on the first chip, where individual ones of the plurality of transmit clusters comprise one of the plurality of FSMs. In an embodiment, a global transmit test generator is communicatively coupled to each of the set of transmit lanes on the first chip, and a global transmit expected response generator is communicatively coupled to each of the plurality of FSMs on the first chip.

The invention provides a personalized learning path recommendation method and device based on enhanced cognitive diagnosis. The method comprises the following steps: constructing a learning behavior heterogeneous graph to describe richer learning behavior characteristics of students; according to a knowledge forgetting simulation algorithm based on reinforcement learning, a training agent learns a knowledge forgetting rule of a student in a learning process according to a reward mechanism; evaluating knowledge cognition levels of the students at different moments according to the learning behavior sequence fused with the forgetting rules of the students; building a knowledge sequential graph by using a finite-state automatic machine so as to build a hyponym and a first-to-second relationship between knowledge points; a learning path recommendation method based on Monte Carlo search enhancement is adopted, and personalized learning paths are recommended for students in an unobservable environment according to the knowledge cognition level and the knowledge sequential diagram. According to the method, the cognitive level of the student can be accurately evaluated, the knowledge sequential graph can be automatically generated, and the real demand of recommending a reasonable and effective personalized learning path to the student in real time in an unobservable environment is met.

The invention provides a voice keyword detection method, a storage medium and electronic equipment, and relates to the technical field of voice signal processing, and the method comprises the steps: determining a phoneme scoring path and a background sound path corresponding to an acoustic feature sequence of a to-be-detected target voice; identifying a noise type corresponding to each noise background sound; constructing an initial first linear grammar finite state converter according to the phoneme scoring path, and configuring a corresponding wildcard arc for the first linear grammar finite state converter by using each extracted noise type to obtain a second linear grammar finite state converter based on noise perception; creating a composite weighted finite state converter through a composite operation; and decoding the composite weighted finite state converter to predict whether the target keyword exists in the target voice. Therefore, the keyword detection system can sense different noise environments, the sensitive degree of the system to noise is dynamically adjusted, and the keyword detection accuracy in the high-noise environment is guaranteed.

Provided are systems and methods for enhancing the output accuracy and consistency of sequence processing models, particularly when generating text that must conform to a specific formal language. Systems and methods can integrate finite-state or push-down automata with the decoding process to ensure that the generated sequences adhere to the desired syntax or grammar rules. A system can generate or otherwise leverage a finite-state or push-down automaton that encodes constraints associated with a particular formal language or syntax. At each decoding iteration of a sequence processing model, the decoding system can use the finite-state or push-down automaton to evaluate the token validity for each of a number of possible output tokens. The output of the sequence processing model can then be limited to or otherwise guided towards tokens that are indicated as valid by the finite-state or push-down automaton.

According to the automatic software development method and device and the computer program, intelligent demand analysis is achieved through a natural language processing technology, dynamic task arrangement is conducted through a finite state automaton, collaborative development is completed by means of a multi-specialized role agent, intelligent verification is implemented based on a template matching mechanism, and the development efficiency is improved. And a complete automatic closed loop from demand to delivery is constructed. According to the scheme, full-process automation is realized, manual intervention is greatly reduced, and the development efficiency is remarkably improved; through division and cooperation of multiple agents, the professionality and decision-making quality of each link are ensured, and the capability limitation of a single agent is overcome; flexible and reliable process control is provided based on state machine management, and development state changes are dynamically adapted; and the standard consistency of the delivery result is ensured by combining template verification. According to the method, the problems of long development period, large quality fluctuation and the like caused by chain splitting, low intelligent level and excessive dependence on manpower of an existing development tool are effectively solved, and a feasible path is provided for comprehensive intelligence of software development.

The invention provides an intelligent question and answer processing method and device, electronic equipment, a computer readable storage medium and a computer program product. The method comprises the steps of obtaining a target question text in response to a received question and answer request, and performing intention analysis on the target question text to obtain an intention analysis result; when it is determined that the target problem text meets a problem dismantling condition based on the intention analysis result, dismantling the target problem text based on the intention analysis result and the target problem text to obtain a plurality of sub-problems; for each sub-problem, determining a first execution plan corresponding to the sub-intention corresponding to the sub-problem, and determining a first execution result corresponding to the sub-problem based on the first execution plan; and based on the first execution result corresponding to each sub-question, performing finite state transition, and determining a reply text corresponding to the target question text. According to the invention, the accuracy and controllability of intelligent question and answer processing can be improved.

The invention discloses a multi-language speech recognition method. A multi-language speech recognition model comprises an encoder, a language classification model, a CTC module and a decoder. The method comprises the following steps: acquiring acoustic features of an audio to be identified, and inputting the acoustic features to the encoder to obtain an encoder output result containing acoustic feature local information and acoustic feature global information; a language classification model carries out preset processing on the encoder output result to obtain a language classification result; the CTC module is combined with a weighted finite state conversion machine, and an encoder output result is mapped to a streaming nbest identification result through a prefix beam search algorithm; and the decoder re-scores the output result of the encoder according to the streaming nbest identification result. The multi-language speech recognition model only shares an encoder at the bottom layer, and the language classification model, the CTC module and the decoder at the top layer are independent. The problem that homophones of different languages are confused in speech recognition is reduced through shared bottom layer parameters and a re-scoring process, and the language classification accuracy is improved.

The invention belongs to a specification mining technology of software engineering, and relates to a construction method of an approximate specification mining model and a software behavior verification system. The construction method comprises the following steps: generating a group of linear temporal logic LTL formulas for describing positive example time sequence attributes according to a positive example set; using an LTL formula to generate a potential negative example for evaluation and training; designing and constructing a neural network for analyzing the finite state automaton from the parameter assignment so as to simulate an acceptance behavior of the finite state automaton; and iteratively searching the neural network through a gradient descent algorithm until the maximum number of iterations is reached, and mining to obtain the finite state automaton. The neural network can simulate acceptance of the finite state automaton in the reasoning process, the finite state automaton can be explained at low cost, and the problem of search space explosion is solved.

The invention discloses a book-based subject knowledge system construction method and device, and the method comprises the steps: representing a directory as a directed tree, and dividing the directed tree into a skeleton module and a plurality of chapter modules; carrying out the association and expansion of a title through a large language model, and generating an abstract; knowledge concepts, subject terms and structural relations in titles in all the modules are extracted and subjected to double correction to obtain a plurality of knowledge system trees, and then a mother tree obtained after the skeleton module is processed and a sub-tree obtained by the chapter module are spliced; and finally, giving a plurality of knowledge trees obtained according to a plurality of groups of book directories in the same subject field, and combining the knowledge trees into a unified knowledge system tree based on a finite-state machine principle. According to the method, the knowledge system is constructed and decoupled into an extraction stage and a fusion stage based on LLM, the problem of a pain point of drifting between knowledge concepts and attributes when a simple chapter title is faced is solved, and strict control on semantic consistency and hierarchical rationality in a path merging process is ensured based on a state machine.

An intelligent decision-making method based on a rule engine and a finite-state machine adopts a QT high-performance cross-platform development framework and a safe and reliable mode of accessing rule data by a memory database. The method mainly comprises metadata management, state node and rule setting management, state space internal transfer setting, state space external transfer setting, rule data acquisition, service execution or circulation scheme acquisition, rule input data real-time acquisition, rule matching, state machine internal state transfer processing, execution action and state space external transfer processing. And calling functions such as an internal state transfer method of the state machine. According to the method, automation and intelligentization of business decision making of a complex system can be achieved, when business rules change, automatic operation of the business state machine in an application system can be achieved without modifying business logic codes, and the transportability of software, the running reliability of the software and the data safety can be improved.

A system provides a language model that utilizes an optimized parser and operates at the byte- level in a context free grammar (CFG) and a tokenizer vocabulary. The CFG is constrained and automatically transformed to a byte-level grammar. A prediction mechanism is used to predict the allowed sequences of bytes that can appear after a given prefix. In some instances, only the next token is constrained so that candidates for the next token can be intersected with tokens in the tokenizer vocabulary. To achieve this, lattice parsing is performed using a finite state automaton (FSA) that is generated and then minimized.

The invention relates to the technical field of intelligent training and data analysis, in particular to an intelligent model construction method and system for student training data analysis. Comprising the following steps: constructing an SOP time sequence knowledge graph, obtaining a standard operation specification document and expert-level operation demonstration data, and constructing the SOP time sequence knowledge graph; real-time feature extraction: capturing a multi-modal data stream, and generating a real-time behavior feature vector; state recognition and path deduction: inputting the real-time behavior characteristics into an event classifier to recognize a key event, performing path deduction based on deterministic finite state automaton logic in an SOP time sequence knowledge graph, and determining and outputting a current state pointer; deviation analysis and judgment: extracting a compliance mask based on a current state, and injecting the compliance mask into a decoding process of the attention network; and performing feedback and adjustment to generate a corresponding deviation event signal. Through deep analysis, feedback is more targeted, and the accuracy and fineness of training evaluation are remarkably improved.

The invention discloses a multi-model cache management algorithm based on online learning, which comprises the following steps: S1, an SSD (Solid State Disk) controller receives an I / O (Input / Output) request sent by an upper-layer application and captures a request feature; s2, after a fixed number of pages are processed every time, the request features are aggregated to generate window-level indexes; s3, performing discretization processing, and mapping into a finite state space; s4, the Q table calculates the predicted value of each strategy in the basic strategy pool in the current state; s5, the online learning module dynamically selects a cache replacement strategy of the next period in the basic strategy pool through the predicted value; and S6, additionally setting a preferential expelling chain table in the cache, monitoring the busy degree of a rear-end flash memory chip in real time by an active write-back module, and asynchronously writing cold dirty pages in the preferential expelling chain table back to the flash memory. According to the method, the cache hit rate is improved through dynamic strategy switching; the active write-back module reduces dirty page replacement delay and prolongs the service life of the SSD; the total memory occupation of the Q table and the Xgboost model is small, and the method adapts to the resource limitation of the embedded controller.

The invention discloses a finite state inquiry method and system based on a large model and a knowledge graph, and relates to the field of business handling, when there is a business handling intention, a finite state machine sets an initial business state, and a large language model analyzes, inputs and extracts keywords and demands to determine a current state; the user naturally converses with the big language model, and the big model is guided to complete the process according to the knowledge graph and the current state; when the user interrupts questions, the large model answers the questions according to the knowledge graph, and then the finite-state machine records the state to help the user to seamlessly return and continue to handle the questions; according to the method, the problem of large model illusion is effectively solved, and the accuracy and stability of user intention judgment are improved; intelligent autonomous business handling without manual intervention is realized; the seamless recovery process after the user interrupts questions at any time is supported, and the flexibility and coherence of business handling are enhanced; comprehensive knowledge coverage is ensured by means of a knowledge graph, and user questions are accurately answered; and meanwhile, the dependence on manual business personnel is reduced, and the labor cost is reduced.

The invention provides a code-free SaaS application rapid development method and system based on data source driving, and the method comprises the steps: constructing a forward business process directed acyclic graph, defining compensation association and reality binding for a forward operation node of the forward business process directed acyclic graph, and generating a visual transaction model; analyzing the transaction model to generate a transaction step sequence, constructing a finite state set and a state transfer function based on the sequence, and packaging the finite state set and the state transfer function into an SAGA process state machine definition object; generating a global transaction ID when a transaction life cycle is started, constructing a transaction context object in combination with the state machine definition object, and serializing to generate an initial transaction context instance; and loading and deserializing the instance, starting a state-driven execution loop, terminating by iterating single-step state transition when the current state belongs to a termination state set, judging a final result of the transaction, and archiving an audit log. According to the method, transaction process modeling and formalized state driving execution are fused, and the method is suitable for SaaS application development of cross-heterogeneous data sources.

The invention relates to the technical field of robot autonomous decision-making, and discloses an underwater robot behavior decision-making method based on a behavior tree, which describes and controls the specific behavior of an underwater robot based on the behavior tree, organizes and manages complex behavior logic through a tree structure, and analyzes a specific task to determine the behavior of the underwater robot. And decomposing into behavior sub-trees, and combining control nodes and action nodes in the behavior sub-trees to complete a specific logic switching function. Compared with a traditional finite-state machine, the method has the advantages of modularization, expandability and high readability, the coupling degree between modules in the sub-tree is low, the sub-tree can be transplanted to multiple positions of the behavior tree, the problem that the workload of the reuse state of the finite-state machine is large is effectively solved, and the method has good practical application value.

A computer-implemented system that reduces and resists computationally generated fraudulent reviews by enforcing aspect-level decomposition with evidence requirements, multi-tier cryptographic verification, and deterministic trust scoring. Reviewer tiers (public, independent reviewer, independent professional reviewer) use verifiable credentials, zero-knowledge purchase proofs, and device or platform attestation. Evidence gates apply fixed, monotonic transformations; mandatory-evidence aspects yield zero contribution absent a required artifact. A finite-state dialog protocol with immutable timer fields enforces typed, aspect-bound objections. A Consumer Trust Board employing threshold signatures issues binding decisions affecting Consumer Trust Score computation with bounded retro-adjustment. A certification registry maintains credentials and sanctions that calibrate weighting. Non-instrumented submissions are badge-ineligible and weight-capped. Uniqueness keys prevent double counting. Dialog records are version-chained and batch-anchored via collision-resistant commitments. All computations use parameters from a versioned configuration to ensure deterministic reproducibility.

The invention discloses a finite-state machine coverage rate statistical method of a VCD (Video Compact Disc) file, which is characterized in that a mapping relationship is established between a signal name and state transition information by directly analyzing a YAML (Young Attribute Markup Language) format file of finite states and transition behaviors among the states compiled in a design stage and adopting a hash table mapping technology, so that the constant-level efficiency of reducing time complexity to O (1) is realized. When the VCD file generated by simulation is processed, two strategic file reading methods are adopted, and the file processing flow is simplified. And the uniqueness and accuracy of data processing are ensured through a self-defined Hash algorithm. In simulation data processing, screening is carried out according to the rule of the first character of the data, and only key state transition information is reserved. According to the method, the defects of processing the VCD file and counting the coverage rate of the finite-state machine under the condition of limited resources in the prior art can be effectively overcome, the counting speed of the coverage rate of the finite-state machine is increased, the efficiency of the verification process is improved, and remarkable performance improvement is brought to the verification stage of integrated circuit design.

The present application provides an anomaly detection system for industrial control systems, encompassing data collection, data processing, anomaly detection, and response execution modules. It uniquely employs a strategy based on Finite State Machines (FSM), actively querying the data collection module to gather operational data from sensors and Programmable Logic Controllers (PLC). The data processing module standardizes and formats the data, while the anomaly detection module uses a predefined FSM model and adaptive learning mechanisms to enhance the accuracy of anomaly identification.

The present application proposes a learning-based SQL automatic generation method, which includes: obtaining a database to be queried and preset target constraints, and constructing a vocabulary required for generating SQL statements according to the database; generating a finite state automaton according to SQL grammar rules; inputting the encoding of the specified initial word into the constructed word selection probability model, obtaining the SQL statement output based on the encoding of the initial word, and calculating the actual benefit value of each word in the SQL statement; calculating the benefit estimation value of the next word through the constructed word selection benefit estimation model and constraint encoding network, and updating the parameters of each constructed network model according to the difference between the actual benefit value and the benefit estimation value; repeating the above steps until the network model converges, and generating the target SQL statement through the trained word selection probability model. The method can automatically generate SQL statements that meet the current constraints, improve the accuracy of generating SQL statements, and reduce costs.

The invention discloses a control method for the operation state of a variable pitch system, which comprises the following steps: abstractly dividing the operation mode of the variable pitch system into an operation state, a shutdown state, a braking state and a maintenance state, and then defining a switching condition for switching to the next state for each state; meanwhile, an FMS (finite state memory) finite-state machine is introduced into an operation program of the variable-pitch system, the operation process is abstracted into a limited number of state machines, each state machine represents different operation modes of the variable-pitch system, and the state of the variable-pitch system can only be in one state machine at any moment; by using the FMS finite-state machine, the use of an if-else complex branch structure is reduced, the complex logic judgment is simplified, the coupling of the operation process of the variable-pitch system is reduced, the reliability of a variable-pitch program is improved, and the maintainability of a variable-pitch application program is improved.

A system includes a device having a controller a plurality of finite state machines (FSMs). The device is to detect that one or more FSMs of the plurality of FSMs fails to satisfy a non-idle duration criterion during an operation, where the one or more FSM that fail to satisfy the non-idle duration criterion are associated with one or more errors. The device is to determine a location of the one or more FSMs that fail to satisfy the non-idle duration criterion. The device is to record the location of the one or more FSMs and the one or more errors, restore the one or more FSM to an idle state, and transmit an indication that the one or more FSMs failed to satisfy the non-idle duration criterion.

The invention discloses a quantum key distribution system and method. According to the system, a phase coherence monitoring mechanism is innovatively introduced, and early attack detection is realized through a dynamic consensus sampling protocol; a zero-trust relay network is constructed by adopting a wavefront fragmentation principle, and trust dependence on relay nodes is eliminated; self-adaptive safety monitoring is realized based on a finite state automaton, and a system safety strategy is dynamically adjusted. According to the method, the problems of resource consumption type attack, relay trust dependence, static protocol limitation and the like faced by an existing QKD system are solved through a strict mathematical framework, and long-distance quantum key distribution with efficient resources, endogenous security and elasticity and physical layer security guarantee is realized. Experiments show that compared with a traditional scheme, the detection delay of the system is reduced by about 38%, the resource waste is reduced by about 40%, and the availability of the system reaches 99.995% or above.

The invention provides a voice generation method and device, a computer readable storage medium and electronic equipment, and the method comprises the steps: obtaining an input text which represents a dialect text of a target small language; converting the input text into a standard text through a finite state conversion model; the standard text is analyzed through the target voice model, audio features of the standard text are obtained, target voice is generated according to the audio features, each group of data in the multiple groups of data comprises historical standard texts and historical audio features, the historical standard texts comprise general texts and special texts, and the historical audio features comprise general audio features. The general text represents the standard language text contained in various languages including the target small language, and the special text represents the standard language text only contained in the target small language. According to the method and the device, the problem that the voice corresponding to the complex small language cannot be accurately generated is solved, and the effect of accurately generating the voice corresponding to the small language is achieved.

The invention belongs to the technical field of artificial intelligence, and particularly relates to a computer network intrusion detection method and system based on artificial intelligence, and the method comprises the steps: constructing a finite state automaton to carry out the state jump compliance verification of a connection flow, intercepting the illegal flow, only sending the compliance flow into a feature engineering module, and extracting the multi-dimensional behavior features; inputting a deep neural network classification model to determine whether the behavior is an intrusion behavior; according to the technical scheme provided by the invention, the data input to the artificial intelligence model can be ensured to have complete compliance on the protocol level, so that the model is prevented from learning false feature association caused by protocol violation, and the antagonistic attack based on protocol state jump can be effectively resisted on the premise of not depending on adversarial training.

The invention belongs to the technical field of aviation safety information processing and intelligent retrieval, particularly relates to an aviation safety knowledge mixed retrieval system based on a creative distributed database, and solves the problem that the prior art cannot meet the requirements of aviation safety information processing accuracy, efficiency and reliability. The method comprises the following steps: firstly, depending on a Peng and Feiteng trust and creative server and an OceanBase distributed database, matching an integrated storage engine and a physical collaborative distribution module, and constructing a multi-type data fusion storage base; then realizing precise semantic retrieval, weak network off-line data management and increment synchronization through double-engine cooperation of an intelligent engine layer, fusion of a domain-specific embedded model and an RRF optimization algorithm and combination of a finite-state machine and a positive and negative counter algorithm; and the application service layer standardizes an API and a multi-tenant isolation strategy, and adapts to multi-terminal and third-party system integration. The accuracy, efficiency and reliability of aviation safety information processing are remarkably improved.

The invention discloses a hardware acceleration method and system for a ZSTD data compression algorithm based on an FPGA. Unified hardware implementation and collaborative optimization are carried out on three key links of LZ77 character matching, Huffman coding and finite state entropy coding in the ZSTD data compression algorithm. According to the system, a multi-channel parallel LZ77 character matching hardware architecture is adopted, and character matching is executed on continuous positions in a plurality of parallel windows at the same time. A modular design and a deep pipeline structure are adopted, and a buffer and pipeline mechanism is introduced among modules such as an LZ77 matching module, a Huffman coding module and a finite state entropy coding module. The 375MB / s compression throughput can be achieved under the 100MHz clock frequency, the compression speed is remarkably increased while the compression ratio is guaranteed, and the method is suitable for scenes with high requirements for compression performance of data centers, edge computing and embedded systems and has high practicability and popularization value.

A text segmentation and sensitive word detection method based on matrix multiplication, comprising the following steps: obtaining an original text string and a sensitive word library; constructing a deterministic finite state automaton tree diagram of sensitive words according to the sensitive word library; converting the original text string into a text character two-dimensional matrix and recording the length of the text character two-dimensional matrix; constructing a matching two-dimensional matrix according to a horizontal matching rule, a vertical matching rule, an oblique matching rule and an inverse oblique matching rule, the length of the matching two-dimensional matrix being the same as that of the text character two-dimensional matrix; performing dot multiplication processing on the text character two-dimensional matrix and the matching two-dimensional matrix to obtain a corresponding result matrix; generating a corresponding matching text string according to the result matrix, and matching with the deterministic finite state automaton tree diagram to determine whether there is a sensitive word. The application supports interval text character information detection, improves the sensitive word detection accuracy and detection efficiency.