579 results about "Finite state" patented technology

A network appliance for monitoring, diagnosing and documenting problems among a plurality of devices and processes (objects) coupled to a computer network utilizes periodic polling and collection of object-generated trap data to monitor the status of objects on the computer network. The status of a multitude of objects is maintained in memory utilizing virtual state machines which contain a small amount of persistent data but which are modeled after one of a plurality of finite state machines. The memory further maintains dependency data related to each object which identifies parent/child relationships with other objects at the same or different layers of the OSI network protocol model. A decision engine verifies through on-demand polling that a device is down. A root cause analysis module utilizes status and dependency data to locate the highest object in the parent/child relationship tree that is affected to determine the root cause of a problem. Once a problem has been verified, a “case” is opened and notification alerts may be sent out to one or more devices. A user interface allows all objects within the network to be displayed with their respective status and their respective parent/child dependency objects in various formats.

A system for analyzing an interactive voice response (IVR) system of a call processing center determines a complete sequence of events occurring within the IVR system. The IVR system being operable to automatically accept calls from callers and respond to input from the callers. The system models a call flow of the IVR system as a non-deterministic finite-state automaton. A recording of a plurality of calls to the call processing center is split, such that each of plural calls to the call center is in one audio file. For a plurality of calls, the system detects a complete sequence of DTMF and/or speech input to the IVR system, detects selected prompts issued by the IVR system, and inputs the detected sequence of DTMF and/or speech input as well as the detected prompts issued by the IVR system into the finite-state automaton to determine a call-event sequence for that call. The call-event sequence includes information regarding how that call left the IVR system.

In a chip-to-chip communication system and apparatus, a set of physical signals to be conveyed over a communication bus is provided, and mapped to a codeword of a vector signaling code using the physical signals and a state information, wherein a codeword is representable as a vector of plurality of real-valued components, and wherein a vector signaling code is a set of codewords in which the components sum to zero and for which there is at least one component and at least three codewords having different values in that component; and wherein the state information is a plurality of information present in continuous or discrete form which may have been obtained from previous codewords transmitted over the communication bus.

Techniques are provided for reducing feedback while maintaining performance in a MIMO-OFDM system. The disclosed techniques employ finite-rate feedback methods that uses vector quantization compression. The disclosed methods/techniques generally involve: receiving a plurality of symbols from a plurality of sub-carriers at a receiver; selecting a plurality of indices of codewords corresponding to a codebook of pre-coding weighting matrices for the sub-carriers based on vector quantization compression of the codewords; and transmitting the selected indices over a wireless channel to a transmitter. Finite state vector quantization feedback makes use of a finite state vector quantizer (FSVQ), which is a recursive vector quantizer (VQ) with a finite number of states. In finite state vector quantization feedback, optimal precoding matrices (beamforming vectors) are selected sequentially across subcarriers. In a trellis-based feedback method, the optimal precoding matrices are selected at the same time for all subcarriers by searching for the optimum choice of matrices along a trellis using the Viterbi algorithm (dynamic programming).

Disclosed is a method and system for multi-character multi-pattern pattern matching. In the multi-character multi-pattern pattern matching method, patterns in an input stream are detected by transitioning between states of a “compressed deterministic finite state automaton (DFA)”, with each transition based on multiple characters of the input stream. The compressed DFA is created by compressing an original DFA, such as an Aho-Corasick DFA, such that each state of the compressed DFA represents multiple consecutive states of the original DFA and each transition between the states of the compressed DFA is a combination of all of the transitions between the multiple consecutive states of the original DFA. This method can be implemented using a Ternary Content-Addressable Memory (TCAM) to store the transitions of the compressed DFA and compares the transitions with multiple characters of an input stream at a time to detect patterns in the input stream.

Memory architecture provides capabilities for high performance content search. The architecture creates an innovative memory that can be programmed with content search rules which are used by the memory to evaluate presented content for matching with the programmed rules. When the content being searched matches any of the rules programmed in the Programmable intelligent Search Memory (PRISM) action(s) associated with the matched rule(s) are taken The PRISM content search memory is embedded in a single core or multi-core processors or in multi-processor systems to perform content search. PRISM accelerates content search by offloading the content search tasks from the processors. Content search rules comprise of regular expressions which are converted to finite state automata and then programmed in PRISM for evaluating content with the search rules.

Finite-state systems and methods allow multiple input streams to be parsed and integrated by a single finite-state device. These systems and methods not only address multimodal recognition, but are also able to encode semantics and syntax into a single finite-state device. The finite-state device provides models for recognizing multimodal inputs, such as speech and gesture, and composes the meaning content from the various input streams into a single semantic representation. Compared to conventional multimodal recognition systems, finite-state systems and methods allow for compensation among the various input streams. Finite-state systems and methods allow one input stream to dynamically alter a recognition model used for another input stream, and can reduce the computational complexity of multidimensional multimodal parsing. Finite-state devices provide a well-understood probabilistic framework for combining the probability distributions associated with the various input streams and for selecting among competing multimodal interpretations.

In various embodiments, a method for processing event streams includes receiving a finite state machine defined in response to a set of processing components, a set of states, and a set of entry points. Event data associated with an event stream is also received. The event data is processes according to the finite state machine to generate an event.

A system includes a plurality of actuators and a management system operably associated with the plurality electronic and mechanical devices. The management architecture includes interfaces configured to the entire electronics and mechanics to provide a parameter to a computer. The computer includes a control and management architecture using modular finite state flow designs configured to analyze the parameter. The computer with a plurality of finite state machines can conduct a plurality of control laws operably associated with one or more actuators for finite functions of mobility. The method includes matching the parameter with the finite state machine and controlling the actuator via control law operably associated with finite state machine. The method can therefore be achieved either manually, semi-autonomously and autonomously with seamless and switchless control using a central control computer with integration of electronic and mechanic sensors and devices.

An attribute-based speech recognition system is described. A speech pre-processor receives input speech and produces a sequence of acoustic observations representative of the input speech. A database of context-dependent acoustic models characterize a probability of a given sequence of sounds producing the sequence of acoustic observations. Each acoustic model includes phonetic attributes and suprasegmental non-phonetic attributes. A finite state language model characterizes a probability of a given sequence of words being spoken. A one-pass decoder compares the sequence of acoustic observations to the acoustic models and the language model, and outputs at least one word sequence representative of the input speech.

An implementation framework, including methodologies and the architecture, for a real-time traffic emulation for packet switched networks. The framework uses extended finite state machines to model the traffic flows that are to be emulated. A simple yet flexible FMS-based scripting language is proposed to describe these flows. An event-driven approach to schedule CPU among flows is also adopted.

The embodiment of the invention provides a voice recognition method, device and system and a terminal. The method comprises the steps that voice to be recognized is received; feature extraction is performed on the voice to be recognized so as to obtain feature information; and the feature information is inputted to a weighted finite state transducer WFST to be recognized, the WFST is obtained by the pre-created combination of an acoustic model, a pronunciation dictionary and a language model, all the first language phonemes and second language phonemes in the acoustic model have the corresponding relationship, and phonetic notation of all the first language vocabularies in the pronunciation dictionary is performed by the second language phonemes. With application of the scheme, the voice recognition accuracy can be enhanced.

A method and apparatus for transforming regular expressions into a less resource intensive representation is disclosed. The method and apparatus converts a collection of regular expressions into a multi-level representation in which the memory requirements of the lowest level representation is reduced when compared with a conventional finite state automaton representation. The method and apparatus converts a collection of regular expressions into a collection of segments and a higher level representation in a way that retains the semantics of the original set of regular expressions. This transformation is performed through the use of an intermediate form. The resulting representation and collection admit an implementation which avoids the potentially costly memory requirements of a traditional implementation of the original expressions.