Relevant bibliographies by topics / ARM Cortex-M3 processor

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'ARM Cortex-M3 processor'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "ARM Cortex-M3 processor"

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Cheng, Shan Ying, Xue Mei Zhou, and Qin Jiang. "An Intelligent Traffic Signal Control System Based on ARM Cortex-M3." Applied Mechanics and Materials 602-605 (August 2014): 1378–82. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.1378.

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In order to alleviate traffic jam, an intelligent traffic signal control system base on ARM Cortex-M3 is implemented. In the system, STM32F207 is processor. Embedded RTOS CoOS is transplanted to achieve multi-task control of traffic signal in software design. A new multi-population genetic algorithm is developed to optimize green ratio. The result analysis shows that the system has stable performance and it makes the optimization of green ratio convenient and swift.
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Oyetoke, Oluwole O. "A Practical Application of ARM Cortex-M3 Processor Core in Embedded System Engineering." International Journal of Intelligent Systems and Applications 9, no. 7 (July 8, 2017): 70–88. http://dx.doi.org/10.5815/ijisa.2017.07.08.

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Mallikarjun, G. "Implementation of True Color Led Display for Video Processing Using Arm Cortex M3 Processor." IOSR Journal of Electronics and Communication Engineering 2, no. 6 (2012): 27–30. http://dx.doi.org/10.9790/2834-0262730.

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Han, Xiao Wei, Jing Lin Duan, and Jian Zhang. "Design of Environmental Monitoring Data Collection Repeater." Advanced Materials Research 955-959 (June 2014): 1112–15. http://dx.doi.org/10.4028/www.scientific.net/amr.955-959.1112.

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A data collection repeater based on ARM Cortex-M3 core for environmental monitoring is introduced in this paper. The chip STM32 is used as CPU processor, CC2530 module as a sink node of Wireless Sensor Networks, the collected data is sent to monitoring center by GPRS network. Integration of WSN, ARM and GPRS, the collection of environmental parameters and capability of wireless transmission are achieved in low-power conditions. Hardware structure and application program of the repeater are given.
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Li, Yun Hong, and Xin Hai Yang. "Design of Generally Remote Transmission System." Key Engineering Materials 480-481 (June 2011): 916–21. http://dx.doi.org/10.4028/www.scientific.net/kem.480-481.916.

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This paper introduces the design of generally remote transmission system with high reliability and multi-transmission-channels. Using a high-speed 32-bit ARM ® Cortex ™ - M3 processor, with multiple network transmission channels, it can be applied to complexly industrial field for reliable data transmission. The system has been successfully applied in Internet of Things of fire networking, which shows that it has high data reliability and a good utility value in the transmission process of the system.
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Pan, Yong, Zi Ye Hou, Jiang Xiong, and Kai Hua Liu. "Research on the System of Radio Frequency Identification and Localization Works in Microwave." Applied Mechanics and Materials 441 (December 2013): 993–96. http://dx.doi.org/10.4028/www.scientific.net/amm.441.993.

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Radio frequency identification and localization is a key technology in the Internet of Things. This paper reports an ARM Cortex-M3 processor based hand-held radio frequency identification and localization terminal and a 8051 processor based active radio frequency tags. The terminal and the tags utilize STM32F103VET6 and the low power consumption STC12LE4052AD as their master controller, respectively. Both of them use Nordic nRF24L01 as their radio frequency identification module. The system works in 2.4GHz ISM microwave band and can read, write and locate radio frequency tags within 20m indoors. The actual measurement of active radio frequency tags shows that this terminal is highly stable and comparable in 2.4GHz microwave frequency radio identification and localization.
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Pan, Yong, Kai Hua Liu, Yi Gao, and Rui Zhao. "A Study on the System of Radio Frequency Identification and Localization Works in UHF." Advanced Materials Research 588-589 (November 2012): 932–35. http://dx.doi.org/10.4028/www.scientific.net/amr.588-589.932.

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This paper designs a hand-held radio frequency identification and localization terminal based on ARM Cortex-M3 processor and active radio frequency tags based on 8051 processor. This terminal uses STM32F103VET6 as its master controller, these tags use STC12C2052AD as their master controller. They all use Nordic nRF905 as their radio frequency identification module. The system works in 433M/868M/915MHz ISM UHF band and can read, write and locate radio frequency tags within 50m indoors. The actual measurement of active radio frequency tags shows that this terminal is highly stable and comparable in 433M/868M/915M ultra-high frequency radio identification and localization. The test results of this system are also analyzed and presented.
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Li, Da Zhai, Zhe Jiang, and Chun Wei Yang. "Design of Control System of Gemstone Processing Machine Based on CAN-Bus." Applied Mechanics and Materials 389 (August 2013): 654–59. http://dx.doi.org/10.4028/www.scientific.net/amm.389.654.

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Aimed at protecting synthetic gemstone processing workers from silicosis that caused by continuously working along machines, a remote-control machine based on CAN-bus is designed. This paper focuses on introducing the hardware and software of its control system. ARM processor STM32F103VET6 with Cortex-M3 core is selected as the MCU, and with the application of motor driver, touch screen and special software, the system can implement auto-operation and manual-operation flexibly. Test data indicates that the control system is stable, easy to operate and suitable to be promoted in factory.
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Chen, Zong Mei. "Design of High-Accuracy Digital Controlled Direct Current Power Supply." Applied Mechanics and Materials 155-156 (February 2012): 298–302. http://dx.doi.org/10.4028/www.scientific.net/amm.155-156.298.

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After introducing the design method of digital current (DC) power supply and the circuit schematic diagram and software flow chart of the key part, the paper designs the core processor based on ARM 32-bit Cortex™-M3 as controller, which, in hardware, has the features of high accuracy and simple circuit, and in function, parameters can be set both through keystroke and computer serial port. Meanwhile, the voltage and current of power supply are of high accuracy, quick in adjust response and with small output voltage ripple.
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Fojtik, Matthew, David Fick, Yejoong Kim, Nathaniel Pinckney, David Money Harris, David Blaauw, and Dennis Sylvester. "Bubble Razor: Eliminating Timing Margins in an ARM Cortex-M3 Processor in 45 nm CMOS Using Architecturally Independent Error Detection and Correction." IEEE Journal of Solid-State Circuits 48, no. 1 (January 2013): 66–81. http://dx.doi.org/10.1109/jssc.2012.2220912.

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Dissertations / Theses on the topic "ARM Cortex-M3 processor"

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Botma, Pieter Johannes. "The design and development of an ADCS OBC for a CubeSat." Thesis, Stellenbosch : Stellenbosch University, 2011. http://hdl.handle.net/10019.1/18040.

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Thesis (MScEng)--Stellenbosch University, 2011.
ENGLISH ABSTRACT: The Electronic Systems Laboratory at Stellenbosch University is currently developing a fully 3-axis controlled Attitude Determination and Control Subsystem (ADCS) for CubeSats. This thesis describes the design and development of an Onboard Computer (OBC) suitable for ADCS application. A separate dedicated OBC for ADCS purposes allows the main CubeSat OBC to focus only on command and data handling, communication and payload management. This thesis describes, in detail the development process of the OBC. Multiple Microcontroller Unit (MCU) architectures were considered before selecting an ARM Cortex-M3 processor due to its performance, power efficiency and functionality. The hardware was designed to be as robust as possible, because radiation tolerant and redundant components could not be included, due to their high cost and the technical constraints of a CubeSat. The software was developed to improve recovery from lockouts or component failures and to enable the operational modes to be configured in real-time or uploaded from the ground station. Ground tests indicated that the OBC can handle radiation-related problems such as latchups and bit-flips. The peak power consumption is around 500 mW and the orbital average is substantially lower. The proposed OBC is therefore not only sufficient in its intended application as an ADCS OBC, but could also stand in as a backup for the main OBC in case of an emergency.
AFRIKAANSE OPSOMMING: Die Elektroniese Stelsels Laboratorium by die Universiteit van Stellenbosch is tans besig om ’n volkome 3-as gestabiliseerde oriëntasiebepaling en -beheerstelsel (Engels: ADCS) vir ’n CubeSat te ontwikkel. Hierdie tesis beskryf die ontwerp en ontwikkeling van ’n aanboordrekenaar (Engels: OBC) wat gebruik kan word in ’n ADCS. ’n Afsonderlike OBC wat aan die ADCS toegewy is, stel die hoof-OBC in staat om te fokus op beheer- en datahantering, kommunikasie en loonvragbestuur. Hierdie tesis beskryf breedvoerig die werkswyse waarvolgens die OBC ontwikkel is. Verskeie mikroverwerkers is as moontlike kandidate ondersoek voor daar op ’n ARM Cortex-M3-gebaseerde mikroverwerker besluit is. Hierdie mikroverwerker is gekies vanweë sy spoed, effektiewe kragverbruik en funksionaliteit. Die hardeware is ontwikkel om so robuust moontlik te wees, omdat stralingbestande en oortollige komponente weens kostebeperkings, asook tegniese beperkings van ’n CubeSat, nie ingesluit kon word nie. Die programmatuur is ontwikkel om van ’n uitsluiting en ’n komponentfout te kan herstel. Verder kan programme wat tydens vlug in werking is, verstel word en vanaf ’n grondstasie gelaai word. Grondtoetse het aangedui dat die OBC stralingverwante probleme, soos ’n vergrendeling (latchup) of bis-omkering (bit-flip), kan hanteer. Die maksimum kragverbruik is ongeveer 500 mW en die gemiddelde wentelbaankragverbruik is beduidend kleiner. Die voorgestelde OBC is dus voldoende as ADCS OBC asook hoof-OBC in geval van nood.
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Books on the topic "ARM Cortex-M3 processor"

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The Definitive Guide to ARM® CORTEX®-M3 and CORTEX®-M4 Processors. Elsevier, 2014. http://dx.doi.org/10.1016/c2012-0-01372-5.

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Book chapters on the topic "ARM Cortex-M3 processor"

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Elahi, Ata, and Trevor Arjeski. "ARM Cortex-M3 Processor and MBED NXP LPC1768." In ARM Assembly Language with Hardware Experiments, 83–95. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11704-1_6.

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Le Corre, Yann, Johann Großschädl, and Daniel Dinu. "Micro-architectural Power Simulator for Leakage Assessment of Cryptographic Software on ARM Cortex-M3 Processors." In Constructive Side-Channel Analysis and Secure Design, 82–98. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89641-0_5.

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YIU, J. "Getting Started with the Cortex-M3 Processor." In The Definitive Guide to the ARM Cortex-M3 TI, 269–81. Elsevier, 2010. http://dx.doi.org/10.1016/b978-1-85617-963-8.00020-x.

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Yiu, Joseph. "Introduction to ARM® Cortex®-M Processors." In The Definitive Guide to ARM® CORTEX®-M3 and CORTEX®-M4 Processors, 1–24. Elsevier, 2014. http://dx.doi.org/10.1016/b978-0-12-408082-9.00001-4.

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"Cortex®-M3/M4 Exceptions Quick Reference." In The Definitive Guide to ARM® CORTEX®-M3 and CORTEX®-M4 Processors, e107-e110. Elsevier, 2014. http://dx.doi.org/10.1016/b978-0-12-408082-9.15004-3.

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Yiu, Joseph. "Using the ARM® CMSIS-DSP Library." In The Definitive Guide to ARM® CORTEX®-M3 and CORTEX®-M4 Processors, 717–35. Elsevier, 2014. http://dx.doi.org/10.1016/b978-0-12-408082-9.00022-1.

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Yiu, Joseph. "ARM® Cortex®-M4 and DSP Applications." In The Definitive Guide to ARM® CORTEX®-M3 and CORTEX®-M4 Processors, 673–716. Elsevier, 2014. http://dx.doi.org/10.1016/b978-0-12-408082-9.00021-x.

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"Cortex®-M3/M4 Debug Components Programmer’s Model." In The Definitive Guide to ARM® CORTEX®-M3 and CORTEX®-M4 Processors, e149-e181. Elsevier, 2014. http://dx.doi.org/10.1016/b978-0-12-408082-9.15007-9.

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Yiu, Joseph. "Getting Started with Keil Microcontroller Development Kit for ARM®." In The Definitive Guide to ARM® CORTEX®-M3 and CORTEX®-M4 Processors, 487–540. Elsevier, 2014. http://dx.doi.org/10.1016/b978-0-12-408082-9.00015-4.

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Yiu, Joseph. "Getting Started with the IAR Embedded Workbench for ARM®." In The Definitive Guide to ARM® CORTEX®-M3 and CORTEX®-M4 Processors, 541–59. Elsevier, 2014. http://dx.doi.org/10.1016/b978-0-12-408082-9.00016-6.

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Conference papers on the topic "ARM Cortex-M3 processor"

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Thenge, Gajanan S., Suhel S. Mulla, and A. B. Patki. "System identification using chaos theory on ARM Cortex M3 processor development board." In 2015 IEEE International Advance Computing Conference (IACC). IEEE, 2015. http://dx.doi.org/10.1109/iadcc.2015.7154811.

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Samotyja, Jacek, and Kerstin Lemke-Rust. "Practical Results of ECC Side Channel Countermeasures on an ARM Cortex M3 Processor." In CCS'16: 2016 ACM SIGSAC Conference on Computer and Communications Security. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2996366.2996371.

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Sobti, Rajeev, G. Geetha, and Sami Anand. "Performance Comparison of Grøestl, JH and BLAKE - SHA-3 Final Round Candidate Algorithms on ARM Cortex M3 Processor." In 2012 International Conference on Computing Sciences (ICCS). IEEE, 2012. http://dx.doi.org/10.1109/iccs.2012.57.

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