74 results about "Spatial complexity" patented technology

A rate control system is disclosed for video coding applications. The rate controller assigns a quantization parameter for video data in a picture in response to complexity indicators indicative of spatial complexity, motion complexity and/or bits per pel of the picture. A virtual buffer based quantizer parameter is proposed based on a virtual buffer fullness analysis and a target rate estimate, which is derived from the complexity indicators. A second quantizer parameter is proposed from a linear regression analysis of quantizer parameters used to code previously coded pictures of similar type (e.g., I pictures, P pictures or B pictures). A coding policy decision unit defines a final quantizer parameter from a comparison of the two proposed quantizer parameters.

The invention discloses a low-complexity polarization code decryption SCL algorithm based on segmented verification assistance, and the algorithm selects a parity check code, repeatedly uses the parity check code in a decryption process, and achieves the performances of SCL-CRC24. Moreover, compared with a conventional scheme, the algorithm is better in low signal to noise ratio anti-noise performance and error rate. In addition, the spatial complexity of the algorithm is lower than that of the SCL-CRC24, the time complexity is greatly reduced, and the decoding speed is greatly improved. Compared with a CRC-24 verification algorithm sacrificing multiple information bits, the algorithm employs a parity check method, enables verification elements to be distributed in the information bits, is repeatedly used in the decoding process, and is lower in time complexity than the prior art.

Perceptual statistics may be used to compute importance maps that indicate which regions of a video frame are important to the human visual system. Importance maps may be applied to the video encoding process to enhance the quality of encoded bitstreams. The temporal contrast sensitivity function (TCSF) may be computed from the encoder's motion vectors. Motion vector quality metrics may be used to construct a true motion vector map (TMVM) that can be used to refine the TCSF. Spatial complexity maps (SCMs) can be calculated from metrics such as block variance, block luminance, SSIM, and edge strength, and the SCMs can be combined with the TCSF to obtain a unified importance map. Importance maps may be used to improve encoding by modifying the criterion for selecting optimum encoding solutions or by modifying the quantization for each target block to be encoded.

An apparatus for spatial sound reproduction comprises a receiver (101) for receiving a multi-channel audio signal. An analyzer (107) determines a spatial property of the multi-channel audio signal, such as a spatial complexity or organization. A selection processor (109) then selects a reproduction mode from a plurality of sound reproduction modes where the multi-channel sound reproduction modes employ different spatial rendering techniques. A reproduction circuit (103) then drives a set of loud-speakers (105) to reproduce the multi-channel audio signal using the selected reproduction mode. The switching between the reproduction modes may be fast (e.g. in the order of 100 ms to 10 secs) thereby allowing a short term adaptation of the reproduction mode to the signal characteristics. The approach may in particular provide an improved spatial experience to a listener.

The invention discloses a message distribution method based on mqtt, a server and a storage medium, and the method comprises the steps of receiving a message sending request broadcasted by a server cluster based on an mqtt protocol, analyzing a to-be-sent message carried in the message sending request to obtain a corresponding theme, and judging whether a first type field exists or not, and judging whether the to-be-sent message is a P2P message if the to-be-sent message exists, judging whether the theme has a second type field or not, determining that the corresponding client has subscribed the theme if the theme has the second type field, and sending the to-be-sent message to the corresponding client. According to the invention, the message sending request is broadcasted based on the mqtt protocol in the server cluster; the message sending request does not need to be stored in each server respectively, the spatial complexity of an algorithm running the message distribution program can be reduced, the client corresponding to the second type field matching can be identified, the time complexity of running an algorithm for searching the corresponding client can be reduced, and the message distribution efficiency is improved.

The invention discloses a dredging process intelligent decision analysis method based on a fuzzy neural control system. The method comprises the steps that 1, data influencing related decision parameters of a dredging construction technology are collected; 2, a matlab principal component analysis method is used to find out the feature thresholds of several decision parameters with the maximum contribution rate; 3, a knowledge base is established; 4, a fuzzy neural control system mechanism is selected and artificial neurons are established, and the number of hidden layers of a neural network is determined according to the dredging complexity; and 5, the fuzzy neural control system is established to carry out assisted decision on dredging construction. According to the invention, the space complexity of the neural network and fuzzy control time complexity are fused, so that the degree of dredging automation is high.

The invention discloses a destination identification method for a plug-in type hybrid vehicle, comprising the steps of obtaining vehicle running state data; and identifying a destination based on a variable-order Markov model. When a destination is not set, the method effectively abstracts the driving habits and rules of a driver according to GPS historic traveling track data, forecasts a destination greater than a confidence coefficient threshold and a path node sequence to the destination, and further estimates the whole vehicle energy consumption of each path node; the method lays the foundation for energy management strategy global optimization, is conductive to increasing automobile dynamic property and economical efficiency, and accords with the energy saving and environmental protection themes of current automobile development. The method uses a PMM algorithm to reduce the space complexity and calculated quantity of a prediction model and a zero frequency problem, utilizes the variable-order Markov model to match automobile historic and current multi-source data, can more flexibly and more accurately predict a destination node and journey sequence, and is of great significance for the intelligent vehicle technology.

The present application relates to electronic commerce technology, and particularly relates to a product clustering method and apparatus. The method comprises: based on similarity between products, sorting out products with similarity meeting a preset condition; determining cluster center products among the sorted out products based on a preset principle; and based on each cluster center product, classifying each non-cluster center product to a same cluster as a cluster center product with highest similarity to the non-cluster center product. The above method is not limited by the number of clusters, the product similarity needs to be calculated only once to construct a similarity network and achieve product clustering progressively based on a heuristic algorithm. In this way, not only the accuracy of the clustering result can be significantly improved, but also time complexity and spatial complexity of the product clustering can be greatly reduced, thus preventing a heavy operation load from being caused to a system and controlling the implementation cost within an ideal range. The method and apparatus are particularly applicable to large-scale product clustering.

The invention relates to a method for large-quantity propylea japonica indoor raising. Wheat aphids, melanaphis sacchari and corn leaf aphids are used as aphids for feeding propylea japonica, and through specific technical measures such as host young aphid cultivating, aphid expanding propagation and propylea japonica artificial feeding, a large quantity of field-preventing and indoor-theory-study propylea japonica is obtained by expanding propagation. According to the method, wheat aphid feeding is carried out at a larval phase, and wheat aphid, melanaphis sacchari and corn leaf aphid feeding is carried out at an adult spawning period. The nutritional requirements of propylea japonica are improved, and the fecundity of propylea japonica is greatly improved. During raising, corn seedlings are placed, the habitat of propylea japonica is enlarged, space complexity is improved, propylea japonica autotomy and competition are lowered, and raising density can be greatly improved. The method is summarized according to the habit of propylea japonica and is easy to operate, economical and practical. Propylea japonica obtained by expanding propagation is high in survival rate and high in fecundity, and large-scale artificial breeding of propylea japonica can be achieved.

The invention provides an automatic discovery method of a complex system oriented MAXQ task graph structure. The method comprises the following steps of: firstly searching state variables influencing actions by adopting a Q-learning exploration environment; then scheduling a clustering algorithm based on the action execution effect, wherein the policy uses a data object as one atomic class, and the atomic classes are aggregated; gradually aggregating the atomic classes to a crescent class until the end condition is met; the process of an aggregation algorithm is as follows: forming a single cluster by each member in the beginning, and combining the adjacent clusters into one cluster in the later iterative process until all the members form one cluster, wherein the time and space complexities are O (n2); combining two clusters through a clustering method, which cannot be separated to the prior state; and (3) obtaining a hierarchical task graph. The method establishes a clustering model by using all learned and perceived information, and automatically constructs the MAXQ task graph through clustering and finally realizes automatic hierarchy of the MAXQ.

The invention provides a rule-based stream data processing method and a rule-based stream data unified monitoring platform. A distributed stream processing framework can be adapted; and rules are dynamically identified, loaded, compiled and sent to a distributed environment, so that matching data is dynamically generated. For complex data and varied business demands, a data generation mode of one-time deployment and flexible rule addition is proposed, and a one-stop data processing platform integrating distributed processing, stream processing, regularization and monitoring is provided, so that the development cost is reduced, the learning difficulty is lowered, and the spatial complexity and the time complexity of data processing are greatly lowered.

The invention discloses a core member identification-based community discovery method. The method comprises the following steps of firstly performing node betweenness center value-based core member identification on nodes in a network, then performing initial clustering, and forming an initial social network structure according to the effects of the nodes in the network; and secondly regarding aninitially clustered node as a node, performing dimension reduction on a similarity matrix M among the nodes to form a new similarity matrix M', and replacing a modularity increment matrix to serve asan input of a CNM algorithm. The core member identification provides a condition for the initial clustering; and the matrix scale can be reduced through the dimension reduction when the similarity among the nodes is calculated, so that the algorithm loss time is shortened. The core member identification algorithm adopts a breadth-first search-based quick betweenness centrality calculation method,and the spatial complexity and the practical complexity of the core member identification algorithm are both lower than those of a conventional algorithm, so that important members in a community network can be quickly located and reasonable division of a social network structure is facilitated.

The invention discloses a high-speed analysis and recovering method for a VPN encrypted channel. The method comprises the steps of high-speed analysis and recovering of a PPTP encrypted channel; high-speed analysis and recovering of an L2TP encrypted channel; and high-speed analysis and recovering of an IPSec active mode channel.The method starts from the bottom-layer protocol of the VPN channel, data link layer and network layer protocols of the VPN are emphatically studied, the security mechanism of the protocol is analyzed, unsafe points during an authentication interaction process and an encrypted transmission process are found, then an analysis and decoding method for the VPN encrypted channel is provided, and sensitive information on the VPN encrypted channel is further recovered in real time. The high performance computation technology in the method can effectively improve the decoding speed, reduces attack time and spatial complexity of encryption algorithms such as RC4 and DES in the VON, and enlarges categories of cracking algorithms by integrating Hashcat source codes.

This invention relates to a distributing Qos multi-case route method based on information entropy in Ad Hoc net, which comprises the following steps: a, determining net model of QoS constraint multi-case method; b, determining information of net state; c, determining the metric of information entropy; d, determining circuit-testing method; f, analyzing space and time complexity. The invention is based on the space and time complexity of information entropy and choosing route in distribution way, which makes the route have better Expandable ability, stability, long life, and be applied in larger scale Ad Hoc net.

The invention relates to a method for acquiring a plurality of reliable communication paths based on the field intensity in a multi-layer wireless network, and belongs to the technical field of wireless communication. First, each node of a wireless network receives radio frequency signals sent by other nodes and acquires neighbor field intensity information; a forward optimal path set and a forward optimal path from a source node to a destination node are acquired through calculation by use of a multi-point shortest path algorithm; a reverse optimal path set and a reverse optimal path from the destination node to the source node are acquired through calculation by use of a multi-point optimal path algorithm; sub-optimal paths are worked out based on a forward optimal path weight and a reverse optimal path weight; and a plurality of optimal paths of the wireless network are determined by testing the optimal paths and the sub-optimal paths. The amount of calculation and the spatial complexity in the process of optimal path acquiring are reduced, the energy consumption of a system is reduced, and the communication reliability of the wireless network is improved.

A weight method-based generation method of complex Nakagami-m fading random sequences includes: according to Nakagami-m fading amplitude and a phase fading distribution function, generating an amplitude random sequence and a phase random sequence by the weight method, and generating a complex random sequence via the amplitude random sequence and the phase random sequence. The method has the advantages that time efficiency and simulation precision are gained via low spatial complexity, generation is achieved by adjusting the number of sample value sampling points and the number of target sequence points according to the need for actual simulation, errors caused by interpolation by the other methods having high precision demands can be avoided, the method is available for the actual simulation of generation of random sequences of any distribution functions having analytical expressions, and the method is of high universality.

The present invention relates to a cyclic update mode-based decision tree construction method. The method comprises: calculating a Bayesian probability by using a target function Pareto optimal value based on time and spatial complexity of the decision tree and the Bayesian theory; modifying a given decision table according to the Bayesian probability; constructing, by using a decision tree selection standard-based calculation method, a decision tree in which a decision table is modified; and applying the decision tree in an information system for automatic decision making, and recording the decision making process. After the system runs for a period of time, a ratio of the automatic decision times of each row in a corresponding decision table to the total decision times of all the rows in the decision table is calculated according to the data of the recorded decision making process, the decision table is modified according to the ratio, a new decision tree of the modified decision table is constructed by using the decision tree selection standard-based calculation method, and the new decision tree is re-applied to the information system. such steps are repeatedly performed until the calculated ratio of each row is less than a decision change probability threshold. The information system employing the technical solution according to the present invention has high-efficiency automatic decision function.

The invention discloses a Qos model construction and Qos strategy scheme operation performance prediction method based on an RTI-DDS. According to the entity classification in the RTI-DDS design, thepresent invention serves as a node of the first dimension of the decision tree, and each node includes a Qos policy corresponding to each part. Within the node, the second dimension is included, and the setting problem of the Qos policy is divided into two parts: the numerical index and the switch configuration, which are respectively transformed into a linear model with time complexity and spatial complexity as an index as a node of the second dimension; And a nonlinear model based on a multivariate decision tree structure, this is the second node of the second dimension. The user can providethe characteristics and indicators of the transmitted data, and derive the appropriate model parameters and Qos strategy from the decision tree node. The model has low complexity, short calculation time and low cost.