Simulink

Simulink® is an environment for multidomain simulation and Model-Based Design for dynamic and embedded systems. It provides an interactive graphical environment and a customizable set of block libraries that let you design, simulate, implement, and test a variety of time-varying systems, including communications, controls, signal processing, video processing, and image processing. Simulink is integrated with MATLAB®, providing immediate access to an extensive range of tools that let you develop algorithms, analyze and visualize simulations, create batch processing scripts, customize the modeling environment, and define signal, parameter, and test data.


References in zbMATH (referenced in 580 articles , 1 standard article )

Showing results 1 to 20 of 580.
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  1. Shafai, Bahram: System identification and adaptive control (to appear) (2024)
  2. Chen, Xue-wen; Zhou, Yue: Modelling and analysis of automobile vibration system based on fuzzy theory under different road excitation information (2018)
  3. Das, Raja; Reddy, Madhu Sudan: Application of recurrent neural network using MATLAB Simulink in medicine (2018)
  4. Fernández-Cara, Enrique; Prouvée, Laurent: Optimal control of mathematical models for the radiotherapy of gliomas: the scalar case (2018)
  5. Jia, Zirui; Liu, Chongxin: Fractional-order modeling and simulation of magnetic coupled boost converter in continuous conduction mode (2018)
  6. Klee, Harold; Allen, Randal: Simulation of dynamic systems with MATLAB and Simulink (2018)
  7. Peixoto, Márcia L. C.; Nepomuceno, Erivelton G.; Martins, Samir A. M.; Lacerda, Márcio J.: Computation of the largest positive Lyapunov exponent using rounding mode and recursive least square algorithm (2018)
  8. Peng, Chao; Zeng, Haibo: Response time analysis of digraph real-time tasks scheduled with static priority: generalization, approximation, and improvement (2018)
  9. Porru, Mario; Serpi, Alessandro; Marongiu, Ignazio; Damiano, Alfonso: Suppression of DC-link voltage unbalance in three-level neutral-point clamped converters (2018)
  10. Yang, Won Young; Choi, Young K.; Kim, Jaekwon; Kim, Man Cheol; Kim, H. Jin; Im, Taeho: Engineering mathematics with MATLAB (2018)
  11. Yu, Hongtao; Langari, Reza: A neural network-based detection and mitigation system for unintended acceleration (2018)
  12. Aditya, Kunwar: Design and characteristics of series-series and series-parallel topologies fed from constant-voltage fixed-frequency supply (2017)
  13. Bavafa-Toosi, Yazdan: Introduction to linear control systems (2017)
  14. Benveniste, Albert; Bourke, Timothy; Caillaud, Benoit; Pagano, Bruno; Pouzet, Marc: A type-based analysis of causality loops in hybrid systems modelers (2017)
  15. Berger, Julien; Mendes, Nathan; Guernouti, Sihem; Woloszyn, Monika; Chinesta, Francisco: Review of reduced order models for heat and moisture transfer in building physics with emphasis in PGD approaches (2017)
  16. Böhme, Thomas J.; Frank, Benjamin: Hybrid systems, optimal control and hybrid vehicles. Theory, methods and applications (2017)
  17. Brandstetter, Pavel; Kuchar, Martin: Sensorless control of variable speed induction motor drive using RBF neural network (2017)
  18. Carpiuc, Sabin-Constantin; Lazar, Corneliu: Modeling of synchronous electric machines for real-time simulation and automotive applications (2017)
  19. Chen, Mingshuai; Ravn, Anders P.; Wang, Shuling; Yang, Mengfei; Zhan, Naijun: A two-way path between formal and informal design of embedded systems (2017)
  20. Costello, Sean; François, Grégory; Bonvin, Dominique: Crosswind kite control -- a benchmark problem for advanced control and dynamic optimization (2017)

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