Roesser state space model is a common multi-dimensional system model based on practical engineering problems. It uses the input of the system and the previous state associated with it to control the current state. The nature of this local calculation not only greatly simplifies the mathematical expression of the multi-dimensional system, but also facilitates the analysis and research of the system. At present, the research based on Roesser model has made some progress . These studies mainly focus on how to design algorithms to make the order of the implementation matrix of the system lower, such as EOA (elementary operation approach) transformation method and P-matrix method . Using lower order implementation matrix to describe the system has strong practical application value, which can not only make the system respond more quickly, but also make the implementation and application of Roesser model in some energy limited systems possible. For example, in wireless sensor networks, the limited energy of sensor nodes is an important problem that puzzles its practical application. The energy consumption of sensor networks is mainly concentrated in the mutual communication between nodes, and its communication energy consumption is 2–4 times of the calculated energy consumption . If each node can process the collected information and then spread it, the whole sensor network will have a longer network lifetime. With the introduction of dynamic system theory into the field of Applied Linguistics, language development can be regarded as a dynamic system, which opens a new perspective for the construction of demand analysis model of language courses. From the perspective of dynamic system theory, based on state space model, language development demand system can be regarded as a dynamic system composed of initial state, target state, system state variables and their dynamic relationship with time. With the rapid development of multimedia technology, multimedia sources can produce a large amount of data. Without data compression, the transmission and storage of multimedia information are difficult to be practical . Multimedia coding and compression can quickly transmit multimedia sources, carry out more services in parallel and reduce storage costs. It is an important research direction in the field of multimedia communication. Multimedia coding is a field that covers many prerequisite courses. Only by mastering the relevant knowledge of random process, information theory and communication principle can we understand and practice the knowledge of multimedia coding . Aiming at this research problem, Jothi S and others try to adopt new theories and new methods to solve the problems in multi-dimensional wireless sensor networks. However, the application of these new theories and methods is not mature, and there are still various deficiencies in the conclusions. Although multidimensional wireless sensor networks have important application prospects in reality, there is no representative application system of multidimensional wireless sensor networks at present, except that some simple regular structure wireless sensor networks are deployed to underwater sensor networks . Swain C and others proposed a new EOA method. The EOA transformation method simplifies the implementation of Roesser state space model into linear transformation operation and specific supplementary operation on multi-dimensional characteristic polynomial matrix. This method is simple in concept and easy to calculate, and can analyze the influence of coefficient correlation on the implementation matrix . Umamaheswari S and others found that each supplementary operation in EOA transformation method can only reduce one order. Although the supplement efficiency can be improved by some decomposition, in fact, only a few transfer functions are suitable for this decomposition method .
Based on the current research, according to the characteristics of space multimedia communication environment and communication equipment, this paper proposes a wireless English synchronous QoS control algorithm with low complexity and easy implementation. Using RTCPSRRTP timestamp and NTP absolute timestamp, the wireless English RTP timestamp is mapped to the same absolute reference clock (sender system time) respectively, and the wireless English synchronization detection decision rule is established according to the synchronization QoS performance requirements between wireless English media. At the receiving end, the wireless English stream is the main media stream and the video stream is the slave media stream. The synchronization detection and judgment is implemented in real time before the video frame is played. The synchronization between audio and video media is realized by corresponding synchronization control of wireless English playback. Simulation results show that the synchronization algorithm effectively improves the synchronization performance between audio and video media in space multimedia communication system and meets the QoS performance requirements of audio and video synchronization in space communication.
In 1990, Perona and Malik proposed a nonlinear anisotropic diffusion equation, namely the P-M model, in order to maintain image edge information. Definitions are as follows:
RTP / RTCP protocol is a network transmission protocol specially designed for real-time media transmission by the wireless English transmission working group of Internet Engineering Task Force (ETF). A synchronization control algorithm between wireless English media based on RTP / RTCP is proposed. The algorithm needs to process each RTCPSR (sender reports) message. The algorithm has high complexity and needs the support of network time protocol (NTP). In addition, the synchronization control is carried out by dropping frames or pausing decoding before wireless English decoding at the receiver, which not only ignores the delay jitter introduced by wireless English decoding, but also affects the normal decoding and reconstruction of video to a certain extent. According to the characteristics of space multimedia communication environment and communication equipment, this paper proposes a wireless English synchronous QoS control algorithm with low complexity and easy implementation .
Using RTCPSRRTP timestamp and NTP absolute timestamp, the wireless English RTP timestamp is mapped to the same absolute reference clock (sender system time) respectively, and the wireless English synchronization detection decision rule is established according to the synchronization QoS performance requirements between wireless English media. Wireless English synchronization control system model at the receiver. At the receiving end, the wireless English stream is the main media stream, and the video stream is the slave media stream. The synchronization detection and judgment are implemented in real time before the video frame is played. The synchronization between audio and video media is realized through the corresponding synchronization control of wireless English playback .
The RTP timestamp corresponds to the sampling time of the first data byte of the payload in the RTP packet. However, wireless English audio and video streams are transmitted in different RTP session streams, so the time stamps in RTP packets in different RTP session streams cannot be directly compared. The reason is that the initial value of the time stamp in the RTP packet is generated randomly, so even if the wireless English audio and video stream is sampled at the same time, the initial time stamp value of the RTP packet is different; The growth of RTP timestamp is monotonic and linear, but its growth rate is related to the media sampling rate. Generally, the sampling rate of wireless English audio and video media is different, so the timestamp growth rate of RTP packets in wireless English audio and video streams is also different. The increment of RTP timestamp in adjacent RTP packets is equal to the number of payload samples in RTP packets. In order to solve the above problems, the RTP timestamp in the wireless English audio and video stream is mapped to a common absolute reference time . Using the relationship between RTP timestamp and NTP absolute timestamp carried in RTCPSR package and RTP timestamp in RTP package, the NTP absolute reference time corresponding to RTP timestamp in wireless English audio and video RTP package is calculated. The receiver can directly compare the calculation results and carry out corresponding synchronous QoS control.
The following formula can be obtained:
Where, R is the RTP timestamp clock frequency, that is, the media data sampling rate. Δ
In the communication process after a call connection is established, the type of wireless English audio and video encoder will not change, so the clock frequency of wireless English audio and video media timestamp will not change, that is, R can be considered as a constant value. The RTP timestamp and NTP timestamp carried by the 1st and i-th RTCPSR packets can be obtained:
The NTP absolute timestamp corresponding to the media package can be obtained from equations (4) and (5):
RFC3550 specification does not require that NTP absolute time in RTCP must be generated by NTP time server, and its specific implementation has exceeded the content of RTP protocol specification. The sender can directly generate the NTP absolute time through any reference clock. Because the implementation of NTP protocol is complex, the system clock of the sender can be used to generate the NTP absolute timestamp value in RTCPSR packet. Through equation (6), the RTP timestamp of audio and video packets is mapped to the same absolute reference clock, that is, the system time of the sender. Therefore, the algorithm in this paper does not need the support of the whole network synchronization clock or NTP protocol, and can directly use the system clock of the sender. It can be seen from equation (6) that the algorithm in this paper only needs to process the NTP absolute time in the first RTCPSR packet as the common clock reference of subsequent audio and video media packets .
Assuming that the Case 1: Case 2: Case 3:
Among them, the time offset of wireless English audio and video is
It can be seen from equation (6) that the wireless English audio and video synchronization algorithm proposed in this paper only needs to process one RTCPSR packet, while the traditional media synchronization algorithm based on RTP / RTCP needs to process multiple RTCPSR packets periodically (such as every 4 / 6 seconds) to continuously update the time stamps in the SR packets used in its algorithm, and its algorithm complexity is directly proportional to the number of SR packets processed. At the same time, this algorithm is easier to implement. Therefore, compared with the traditional media synchronization algorithm based on RTP / RTCP, this algorithm has lower algorithm complexity. In addition, the wireless English audio and video synchronization algorithm proposed in this paper also has the following characteristics:
Without the support of the whole network synchronization clock or NTP protocol, the system clock of the sender can be directly used. It is not affected by packet loss and can be applied to the environment with high packet loss rate of space communication. Media synchronization technology based on RTP / RTCP protocol is a relative timestamp synchronization technology based on time axis synchronization description model. Wireless English audio and video media objects are independently associated with a common time axis. The loss of any RTP packet will not affect the synchronization control of other media packets. If the first RTCPSR packet is lost, the next SR packet can be received as the first RTCPSR packet. Without feedback mechanism, it can be applied to the space communication network environment with long time delay .
System model is a mathematical model that reflects the causal relationship and transformation relationship between system variables. The commonly used mathematical models of discrete systems mainly include difference equation, transfer function model and state space model. Difference equation is a common mathematical model in one-dimensional system, but this model is not suitable for multi-dimensional system. The more complex the multidimensional system is, the higher the dimension of the system is. The higher the order of the difference equation (Discrete System) or differential equation (continuous time or space system) describing the system by the relationship between input and output is, the more difficult the system analysis is. Transfer function is the main mathematical model describing the system characteristics in classical control theory. It is suitable for the linear constant system of single input and single output (SISO). It can easily deal with the transient response analysis or frequency method analysis and design of this kind of system. However, this model is not suitable for multi input and multi output (MIMO) systems, time-varying systems and nonlinear systems. In addition, the transfer function is only an incomplete description of the system. It can only reflect the linear dynamic characteristics of the transfer between the input and output of the system, but can not reflect the dynamic change characteristics within the system, which greatly limits the application of the transfer function model in practice. The state space model is based on the analysis of the internal structure of the system, which is composed of the state equation describing the dynamic characteristics of the system and the output equation describing the transformation relationship between the system output variables and the state variables. It can reflect the changes of all independent variables in the multi-dimensional system, and then determine all internal motion states of the system . Therefore, the state space model reflects all the information of the system dynamic behavior and is a complete description of the system behavior. The state space model has a wide range of applications. It is not only suitable for SISO linear constant systems, but also suitable for nonlinear systems, time-varying systems, MIMO systems and stochastic systems. For different systems, the mathematical expression is simple and unified. The more outstanding advantage is that the state space model adopts local calculation and uses the state variables inside the system to describe its dynamic characteristics. This property of local calculation not only greatly simplifies the mathematical expression of multi-dimensional system, but also facilitates the analysis and research of the system.
At present, the most representative state space models are Roesser model and Fornasini Marchesini model. Multidimensional Roesser state space model is based on the multidimensional system corresponding to the one-dimensional state space model of discrete-time system. It is a model established after the evolution of multidimensional system. The current input and the previous state of the system are associated with this control. Roesser state space model of one-dimensional discrete system is:
Where, u and y represent the input and output of the system respectively, and A, B, C and D are coefficient matrices. Formula and formula are the state equation describing the dynamic characteristics of the system and the output equation describing the transformation relationship between the system output variables and state variables. The two-dimensional Roesser state space model was first proposed by Roesser when he studied multi-dimensional linear filter networks in the 1970s. The Roesser state space model of single input and single output of two-dimensional linear discrete system is:
Extending the two-dimensional Roesser model in the horizontal and vertical directions to the multi-dimensional system, the Roesser state space model with multi-dimensional single input and single output is obtained as follows:
The number of rows of local state
For n-dimensional transfer function:
If matrices A, B, C and d make the formula or formula valid, then a, B, C and D are the Roesser model implementation matrix of the given transfer function.
In the Roesser model with single input and single output, input
The air link rate of the wireless transceiver is 512Kbps. In the experiment, the video is encoded based on H.264 and the audio is encoded based on G.729 Speech coding standard. The audio and video parameters in the experiment are shown in Table 1.
Audio and video parameters
|Encoder||Bit rate||Frame rate||Format|
|Audio||G 729A||8kbps||100fps||8KHz 16-bit|
The duration of each test is 5000 frames of video. The synchronization control algorithm between wireless English media based on RTP / RTCP and the synchronization algorithm proposed in this paper are used for audio and video synchronization. The RMSE results before and after audio and video synchronization are shown in Table 2, Figure 1 and Figure 2.
RMSE before and after synchronization
|Before synchronization||96.26||78.22||176||141.7||90 49||74.12||79.02|
|Inter media synchronization control algorithm||40.19||37.06||40.01||39.05||41.09||37.64||39.09|
|Algorithm in this paper||38.9||36.49||39.25||38.98||38.97||37.17||38.83|
As shown in Table 2, compared with that before synchronization, the RMSE value after adopting the synchronization algorithm in this paper is reduced by 60.09% on average and 77.69% at the highest; Compared with the wireless English media synchronization control algorithm based on RTP / RTCP, the synchronization performance of this algorithm is better than the wireless English media synchronization control algorithm. The RMSE value is reduced by 2% on average and 5.2% at most. In addition, the synchronization control algorithm between wireless English media performs synchronization control by losing frames or pausing decoding before video decoding at the receiver, which affects the quality of wireless English video decoding and reconstruction.
This paper presents the analysis of wireless English multimedia communication based on spatial state model equation. The system model is a mathematical model that reflects the causal relationship and transformation relationship between system variables. The commonly used mathematical models of discrete systems mainly include difference equation, transfer function model and state space model. Difference equation is a common mathematical model in one-dimensional system, but this model is not suitable for multi-dimensional system. The more complex the multidimensional system is, the higher the dimension of the system is. The higher the order of the difference equation (Discrete System) or differential equation (continuous time or space system) describing the system by the relationship between input and output is, the more difficult the system analysis is. Space multimedia communication has the characteristics of high packet loss rate, long transmission time, large jitter and limited resources. In order to meet the QoS requirements of wireless English audio and video synchronization, a wireless English audio and video real-time synchronization algorithm based on RTP / RTCP protocol is proposed. The audio stream is the main media stream, and the wireless English audio and video synchronization is realized by controlling video playback. The algorithm does not need the whole network synchronous clock and feedback mechanism, has low algorithm complexity, and is suitable for spatial multimedia communication. Simulation results show that the synchronization algorithm effectively improves the synchronization performance between audio and video media in space multimedia communication system and meets the QoS performance requirements of audio and video synchronization in space communication. The research of this paper still has many places worthy of further study. Theoretically, we need to deeply analyze and compare the implementation methods of various multidimensional systems, so as to propose a new method to implement Roesser state space model. The application of Roesser in wireless sensor networks needs to be improved.
Audio and video parameters
|Encoder||Bit rate||Frame rate||Format|
|Audio||G 729A||8kbps||100fps||8KHz 16-bit|
RMSE before and after synchronization
|Before synchronization||96.26||78.22||176||141.7||90 49||74.12||79.02|
|Inter media synchronization control algorithm||40.19||37.06||40.01||39.05||41.09||37.64||39.09|
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Neural Network in Vibration Control of Civil Engineering Structure Optimal Model Combination of Cross-border E-commerce Platform Operation Based on Fractional Differential Equations The influence of accounting computer information processing technology on enterprise internal control under panel data simultaneous equation Research on Stability of Time-delay Force Feedback Teleoperation System Based on Scattering Matrix BIM Building HVAC Energy Saving Technology Based on Fractional Differential Equation Construction of comprehensive evaluation index system of water-saving irrigation project integrating penman Montei the quation Human Resource Management Model of Large Companies Based on Mathematical Statistics Equations Data Forecasting of Air-Conditioning Load in Large Shopping Malls Based on Multiple Nonlinear Regression Analysis of technical statistical indexes of college tennis players under the win-lose regression function equation Automatic extraction and discrimination of vocal main melody based on quadratic wave equation Analysis of wireless English multimedia communication based on spatial state model equation Optimization of Linear Algebra Core Function Framework on Multicore Processors Application of hybrid kernel function in economic benefit analysis and evaluation of enterprises Research on classification of e-commerce customers based on BP neural network The Control Relationship Between the Enterprise's Electrical Equipment and Mechanical Equipment Based on Graph Theory Mathematical Modeling and Forecasting of Economic Variables Based on Linear Regression Statistics Nonlinear Differential Equations in Cross-border E-commerce Controlling Return Rate 3D Mathematical Modeling Technology in Visualized Aerobics Dance Rehearsal System Fractional Differential Equations in Electronic Information Models BIM Engineering Management Oriented to Curve Equation Model Leakage control of urban water supply network and mathematical analysis and location of leakage points based on machine learning Analysis of higher education management strategy based on entropy and dissipative structure theory Prediction of corporate financial distress based on digital signal processing and multiple regression analysis Mathematical Method to Construct the Linear Programming of Football Training Multimedia sensor image detection based on constrained underdetermined equation The Size of Children's Strollers of Different Ages Based on Ergonomic Mathematics Design Application of Numerical Computation of Partial Differential Equations in Interactive Design of Virtual Reality Media Stiffness Calculation of Gear Hydraulic System Based on the Modeling of Nonlinear Dynamics Differential Equations in the Progressive Method Knowledge Analysis of Charged Particle Motion in Uniform Electromagnetic Field Based on Maxwell Equation Relationship Between Enterprise Talent Management and Performance Based on the Structural Equation Model Method Term structure of economic management rate based on parameter analysis of estimation model of ordinary differential equation Influence analysis of piano music immersion virtual reality cooperation based on mapping equation Chinese painting and calligraphy image recognition technology based on pseudo linear directional diffusion equation Label big data compression in Internet of things based on piecewise linear regression Animation character recognition and character intelligence analysis based on semantic ontology and Poisson equation Design of language assisted learning model and online learning system under the background of artificial intelligence Study on the influence of adolescent smoking on physical training vital capacity in eastern coastal areas Application of machine learning in stock selection Comparative analysis of CR of ideological and political education in different regions based on improved fuzzy clustering Action of Aut( G) on the set of maximal subgroups of p-groups The internal mechanism of corporate social responsibility fulfillment affecting debt risk in China: analysis of intermediary transmission effect based on degree of debt concentration and product market competitive advantage Study on transmission characteristics in three kinds of deformed finlines based on edge-based finite element method Asymptotic stability problem of predator–prey system with linear diffusion Research on loyalty prediction of e-commerce customer based on data mining Algebraic Equations in Educational Model of College Physical Education Course Education Professional English Translation Corpus Under the Binomial Theorem Coefficient Geometric Tolerance Control Method for Precision Machinery Based on Image Modeling and Novel Saturation Function Retrieval and Characteristic Analysis of Multimedia Tester Based on Bragg Equation Semiparametric Spatial Econometric Analysis of Household Consumption Based on Ordinary Linear Regression Model Video adaptive watermark embedding and detection algorithm based on phase function equation English Learning Motivation of College Students Based on probability Distribution Scientific Model of Vocational Education Teaching Method in Differential Nonlinearity Research on mobile Awareness service and data privacy Protection based on Linear Equations computing protocol Vocal Music Teaching Model Based on Finite Element Differential Mathematical Equations Studying a matching method combining distance proximity and buffer constraints The trend and influence of media information Propagation based on nonlinear Differential equation Research on the construction of early warning model of customer churn on e-commerce platform Evaluation and prediction of regional human capital based on optimised BP neural network Study on inefficient land use determination method for cities and towns from a city examination perspective A sentiment analysis method based on bidirectional long short-term memory networks A study of local smoothness-informed convolutional neural network models for image inpainting Mathematical Calculus Modeling in Improving the Teaching Performance of Shot Put Application of Nonlinear Differential Equation in Electric Automation Control System Higher Mathematics Teaching Curriculum Model Based on Lagrangian Mathematical Model Computational Algorithm to Solve Two–Body Problem Using Power Series in Geocentric System Decisions of competing supply chain with altruistic retailer under risk aversion Optimization of Color Matching Technology in Cultural Industry by Fractional Differential Equations The Marketing of Cross-border E-commerce Enterprises in Foreign Trade Based on the Statistics of Mathematical Probability Theory Application of Linear Partial Differential Equation Theory in Guiding Football Scientific Training Nonlinear Channel Estimation for Internet of Vehicles Some Necessary Conditions for Feedback Functions of de Bruijn Sequences The Evolution Model of Regional Tourism Economic Development Difference Based on Spatial Variation Function System Model of Shipping Enterprise Safety Culture Based on Dynamic Calculation Matrix Model An empirical research on economic growth from industrial structure optimisation in the Three Gorges Reservoir area The Inner Relationship between Students' Psychological Factors and Physical Exercise Based on Structural Equation Model (SEM) Analysis and Research on Influencing Factors of Ideological and Political Education Teaching Effectiveness Based on Linear Equation Study of agricultural finance policy information extraction based on ELECTRA-BiLSTM-CRF Fractional Differential Equations in Sports Training in Universities Examination and Countermeasures of Network Education in Colleges and Universities Based on Ordinary Differential Equation Model Innovative research of vertical video creation under the background of mobile communication Higher Education Agglomeration Promoting Innovation and Entrepreneurship Based on Spatial Dubin Model Chinese-English Contrastive Translation System Based on Lagrangian Search Mathematical Algorithm Model Genetic algorithm-based congestion control optimisation for mobile data network