442 results about "State sequence" patented technology

Procedures are described for enhancing target system execution integrity determined by power fingerprinting (PFP): by integrating PFP into the detection phase of comprehensive defense-in-depth security; by deploying a network of PFP enabled nodes executing untrusted devices with predefined inputs forcing a specific state sequence and specific software execution; by embedding module identification information into synchronization signaling; by combining signals from different board elements; by using malware signatures to enhance PFP performance; by automatic characterization and signature extraction; by providing secure signature updates; by protecting against side-channel attacks; performing real-time integrity assessment in embedded platform by monitoring their dynamic power consumption and comparing it against signatures from trusted code, including pre-characterizing power consumption of the platform by concentrating on trace sections carrying the most information about the internal execution status; by using PFP from sequence of bit transitions to detect deviations from authorized execution of software in a digital processor.

The invention relates to a heterogeneous multi-agent collaborative decision-making method based on a depth deterministic policy gradient, belonging to the collaborative decision-making field of a heterogeneous intelligent unmanned system, comprising the following steps of: firstly, defining heterogeneous multi-agent characteristic attributes and reward and punishment rules, defining multi-agent state space and action space, and constructing multi-agent motion environment for collaboratively making decision; then, establishing an actor module for decision-making action and a critic module for evaluating feedback based on the depth-deterministic strategy gradient algorithm, and training the parameters of the learning model; using the trained model to obtain the multi-agent state sequence; and evaluating the situation of the multi-agent motion state sequence according to the reward and punishment rules set in the environment. The invention may construct reasonable sports environment according to actual needs, achieve the purpose of intelligent sensing and strategy optimization through the synergy between multiple agents in the system, and has a positive effect on the development of the unmanned system field in China.

An electronic device and method are disclosed herein. The electronic device includes a touchscreen, a wireless communication circuit, a microphone, a processor and memory storing instructions implementing the method, including: receiving a first user input including a request to perform a task, transmitting first data associated with the first user input to an external server, receiving a sequence of states executable to perform the task, detecting whether at least one first parameter is omitted from the first user input based on whether execution type information is received with the sequence of states, when the execution type information is received, displaying a graphical user interface (GUI) including at least one input field requesting input of the at least one first parameter, and when the execution type information is not received from the external server, executing a portion of the sequence of states to perform a portion of the task.

The invention relates to the field of the intelligent transportation system, and especially relates to short-term traffic flow forecasting with use of a parameter value sequence of a road segment. A short-term traffic flow forecasting method based on a hidden Markov model comprises the following steps: collected data are processed and counted; a prediction window is set; a starting time measured value of the prediction window, and an average parameter value and a sequence contrast ratio in the prediction window are discretized, so as to form a hidden state and an observation state set of the hidden Markov model; and a Baum Welch algorithm combined with training data are used for learning the model parameter. Finally, for a certain prediction window, a Viterbi algorithm is used to obtain an optimal hidden state sequence based on a known observation state sequence, and a last state of the optimal hidden state sequence is a prediction state. The short-term traffic flow forecasting method based on the hidden Markov model can be used to predict the short-term traffic state in the future, and is an effective method of prediction of the short-term traffic state.

A single combination task lamp and flashlight, providing separate flood and spot light beams, independently controlled in a three-state sequence by simple push button switches. The two kinds of light beams are produced by separate arrays of compact light emitting devices. both arrays are driven by a single, rechargeable battery powered electrical circuit that provides separate, regulated constant currents to the respective arrays of LEDs. the optics and electronics are constructed in a single, ruggedized, compact module. The module is enclosed within a slim, rugged housing and easily field replaceable with minimal tools.

The invention provides a speech recognition model establishing method based on bottleneck characteristics and a multi-scale and multi-headed attention mechanism, and belongs to the field of model establishing methods. A traditional attention model has the problems of poor recognition performance and simplex attention scale. According to the speech recognition model establishing method based on thebottleneck characteristics and the multi-scale and multi-headed attention mechanism, the bottleneck characteristics are extracted through a deep belief network to serve as a front end, the robustnessof a model can be improved, a multi-scale and multi-headed attention model constituted by convolution kernels of different scales is adopted as a rear end, model establishing is conducted on speech elements at the levels of phoneme, syllable, word and the like, and recurrent neural network hidden layer state sequences and output sequences are calculated one by one; and elements of the positions where the output sequences are located are calculated through decoding networks corresponding to attention networks of all heads, and finally all the output sequences are integrated into a new output sequence. The recognition effect of a speech recognition system can be improved.

A method and apparatus are disclosed for improving the processing time of reduced complexity sequence estimation techniques, such as reduced state sequence estimation. Precomputing the branch metrics for all possible symbol combinations in the channel memory makes it possible to remove the branch metrics unit and decision-feedback unit from the feedback loop, thereby reducing the critical path. A set of multiplexers select the appropriate branch metrics based on the survivor symbols in the corresponding survivor path cells. The computational load of the precomputations is reduced for multi-dimensional trellis codes by precomputing each dimension of the multi-dimensional trellis code separately. A hybrid survivor memory architecture is also disclosed for a RSSE for a channel having a channel memory of length L, where the survivors corresponding to the L past decoding cycles are stored in a register exchange architecture (REA), and survivors corresponding to later decoding cycles are stored in a trace-back architecture (TBA) or REA.

The present video tracking technique outputs a Maximum A Posterior (MAP) solution for a target object based on two object templates obtained from a start and an end keyframe of a whole state sequence. The technique first minimizes the whole state space of the sequence by generating a sparse set of local two-dimensional modes in each frame of the sequence. The two-dimensional modes are converted into three-dimensional points within a three-dimensional volume. The three-dimensional points are clustered using a spectral clustering technique where each cluster corresponds to a possible trajectory segment of the target object. If there is occlusion in the sequence, occlusion segments are generated so that an optimal trajectory of the target object can be obtained.

A method and system are directed to enabling a detector to perform relatively accurate channel estimates on blocks of data that include relatively short training sequences in wireless communication signals. Channel re-estimation is performed by transferring the estimation calculations from the time domain into a channel state domain. In one embodiment, information obtained from known training sequences and unknown data may be combined to generate an initial channel estimate. An embodiment of a new recursive Expectation Maximization (EM) process generally i) initializes the EM process with the initial channel estimate; ii) determines updates for the channel estimates; iii) produces a reduced observation vector; iv) generates a special sequence of channel states; v) rearranges each channel state estimate in the reduced observation vector; vi) generates a low-dimensional channel model matrix inversion based on the generated special sequence of channel states; and vii) generates channel estimates based on the generated matrix inversion.

A single combination task lamp and flashlight instrument, providing separate flood and spot light beams, independently controlled in a three-state sequence by simple push button switches. The two kinds of light beams are produced by separate arrays of compact light emitting devices. both arrays are driven by a single, rechargeable battery powered electrical circuit that provides separate, regulated constant currents to the respective arrays of LEDs. The optics and electronics are constructed in a single, ruggedized, compact module. The module is enclosed within an elongated handle that positions the center of mass for optimum balance of the instrument and the control switches for convenient operation according to the sense of touch.

The invention discloses a method for making temperature early warning for a wind generating set based on BootStrap confidence coefficient calculation and a system of the method, and belongs to the field of wind generating sets. The method includes the following steps that real-time data is preprocessed, and working condition recognition is performed on a real-time data variable and multiple divided sub working conditions in a preset database; under the corresponding sub working conditions, real-time temperature data is subjected to data state marking through a designated threshold value limit,abnormal point marks and normal marks are included, and a state sequence in a time sequence is formed; for the state marking sequence formed in the time sequence, the number Nn of the abnormal pointmarks of N continuous data is counted, and an abnormity rate eta is calculated; the triggering condition of confidence coefficient calculation is a preset abnormity rate limit value etaa, and when theabnormity rate eta exceeds the abnormity rate limit value etaa, BootStrap confidence coefficient calculation is triggered, so that the level of a confidence coefficient is calculated; when the levelof the confidence coefficient exceeds an early warning index CLlimit, failure early warning is performed. Calculation of the abnormity rate and calculation of the level of confidence are integrated, so that the rate of a false alarm is greatly decreased.

A joint detection-decoding receiver using a multistage parallel interference canceller for selectively estimating a partial codeword corresponding to a state transition (branch) is disclosed. The JDD receiver of the DS-CDMA system includes a PIC that employs a state sequence to selectively carry out a symbol estimation of a partial codeword corresponding to the branch so as to reduce complexity and a calculation load as well as maintaining a high performance of the receiver according to the joint detection-decoding.

The invention relates to a risk control method for deducing an illegal behavior of medical insurance through data analysis, and the method comprises the steps: 1, obtaining the current and historicalclinical consultation behavior data of a risk control object and the personal information and public data correlated with the risk control object; 2, obtaining the features correlated with the clinical consultation behavior of the risk control object from the data obtained at step 1; 3, classifying the clinical consultation behavior of each clinical consultation in the current and historical clinical consultation behaviors of the risk control object into a corresponding clinical consultation class according to the extracted features, and forming a clinical consultation class sequence; 4, taking the clinical consultation class sequence formed at step 3 as an observation sequence, taking a clinical consultation purpose as a hidden state, calculating the most possible hidden state sequence according to a hidden Markov model, wherein the most possible hidden state sequence comprises the most possible clinical consultation purpose of the risk control object; 5, outputting the medical data correlated with the current and historical clinical consultation behaviors of the risk control object if the most possible clinical consultation purpose, in the hidden state sequence, of the risk control object is corresponding to an abnormal purpose.

The invention belongs to the field of wireless communication, and discloses a key generation method capable of ensuring the security of wireless communication. The key generation method is based on a wireless channel reciprocity and a curve fitting method, extracts a shared key of wireless communication users from a shared wireless channel state to ensure the communication security, and specifically comprises five steps consisting of channel state estimation, pretreatment, quantization and coding, information coordination and privacy amplification; after the treatment of privacy amplification, a generated bit string can be used as a final shared key for transmitting and receiving parties, for protection the subsequent communication security. According to the method, the problem that a difference exists between channel state sequences collected by the transmitting and receiving parties can be solved, key negotiation and whole key generation efficiency are ensured, and the method can be more widely applied to various complex actual application scenarios, for efficiently ensuring the communication security.

Portions of an input measurement sequence are classified into a plurality of regimes by associating each of a plurality of dynamic models with one a switching state such that a model is selected when its associated switching state is true. In a Viterbi-based method, a state transition record is determined, based on the input sequence. A switching state sequence is determined by backtracking through the state transition record. Finally, portions of the input sequence are classified into different regimes, responsive to the switching state sequence. In a variational-based method, the switching state at a particular instance is also determined by a switching model. The dynamic model is then decoupled from the switching model. Parameters of the decoupled dynamic model are determined responsive to a switching state probability estimate. A state of the decoupled dynamic model corresponding to a measurement at the particular instance is estimated, responsive to the input sequence. Parameters of the decoupled switching model are then determined responsive to the dynamic state estimate. A probability is estimated for each possible switching state of the decoupled switching model. A switching state sequence is determined based on the estimated switching state probabilities. Finally, portions of the input sequence are classified into different regimes, responsive to the determined switching state sequence.

A method and apparatus are provided for using the uncertainty of a noise-removal process during pattern recognition. In particular, noise is removed from a representation of a portion of a noisy signal to produce a representation of a cleaned signal. In the meantime, an uncertainty associated with the noise removal is computed and is used with the representation of the cleaned signal to modify a probability for a phonetic state in the recognition system. In particular embodiments, the uncertainty is used to modify a probability distribution, by increasing the variance in each Gaussian distribution by the amount equal to the estimated variance of the cleaned signal, which is used in decoding the phonetic state sequence in a pattern recognition task.