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신경망 상태공간 모델
시스템의 비선형 상태공간 실현을 정의하는 함수를 나타내기 위해 신경망 사용
라이브 편집기 작업
신경망 상태공간 모델 추정 | Estimate neural state-space model in the Live Editor (R2023b 이후) |
함수
createMLPNetwork | Create and initialize a Multi-Layer Perceptron (MLP) network to be used within a neural state-space system (R2022b 이후) |
nssTrainingOptions | Create training options object for neural state-space systems (R2022b 이후) |
nlssest | Estimate nonlinear state-space model using measured time-domain system data (R2022b 이후) |
generateMATLABFunction | Generate MATLAB functions that evaluate the state and output functions of a neural state-space object, and their Jacobians (R2022b 이후) |
idNeuralStateSpace/evaluate | Evaluate a neural state-space system for a given set of state and input values and return state derivative (or next state) and output values (R2022b 이후) |
idNeuralStateSpace/linearize | Linearize a neural state-space model around an operating point (R2022b 이후) |
sim | Simulate response of identified model |
객체
idNeuralStateSpace | Neural state-space model with identifiable network weights (R2022b 이후) |
nssTrainingADAM | Adam training options object for neural state-space systems (R2022b 이후) |
nssTrainingSGDM | SGDM training options object for neural state-space systems (R2022b 이후) |
블록
Neural State-Space Model | Simulate neural state-space model in Simulink (R2022b 이후) |
도움말 항목
- About Identified Nonlinear Models
Dynamic models in System Identification Toolbox™ software are mathematical relationships between the inputs u(t) and outputs y(t) of a system.
- Neural State-Space Model of SI Engine Torque Dynamics
This example describes reduced order modeling (ROM) of the nonlinear torque dynamics of a spark-ignition (SI) engine using a neural state-space model.
- Neural State-Space Model of Simple Pendulum System
This example shows how to design and train a deep neural network that approximates a nonlinear state-space system in continuous time.