Implementation of USB in Embedded Systems Based on ARM Microprocessor

2014 ◽  
Vol 596 ◽  
pp. 883-887
Author(s):  
Xin Li Li
Keyword(s):  
Embedded Systems ◽  
Embedded System ◽  
Hardware Design ◽  
Implementation Process ◽  
Cost Effective ◽  
Software Implementation ◽  
Application System ◽  
Arm Microprocessor ◽  
Working Principle

S3C4510B is a cost-effective 16/32 bit RISC microcontroller based on Ethernet application system, and ISP1161 is a chip which is designed to implement USB protocol in an embedded system. Here, we design and implement embedded systems USB with ISP1161 chip based on ARM microprocessor S3C4510B. This paper describes the basic working principle of ISP1161 chip and hardware design of the system, and presents the software implementation process of USB in embedded systems.

A FRAMEWORK FOR OBJECT-ORIENTED EMBEDDED SYSTEM DEVELOPMENT BASED ON OO-ASIPS

2008 ◽  
Vol 17 (06) ◽  
pp. 973-993 ◽  
Author(s):  
NASER MOHAMMADZADEH ◽  
SHAAHIN HESSABI ◽  
MAZIAR GOUDARZI ◽  
MAHDI MALAKI
Keyword(s):  
Embedded Systems ◽  
Embedded System ◽  
System Development ◽  
Implementation Process ◽  
Object Oriented ◽  
Smooth Transition ◽  
Implementation Framework ◽  
Design And Implementation ◽  
Performance Penalty ◽  
High Level

The growing complexity of today's embedded systems demands new methodologies and tools to manage the problems of analysis, design, implementation, and validation of complex-embedded systems. Focusing on this issue, this paper describes a design and implementation toolset using our ODYSSEY methodology, which advocates object-oriented (OO) modeling of embedded systems and its ASIP-based implementation. The proposed approach promotes a smooth transition from high-level object-oriented specification to the final embedded system, which is composed of hardware and software components. The transition from higher to lower abstraction levels is facilitated by the use of our GUI, which supports the intermediate steps of the design and implementation process. In order to illustrate the proposed approach and related toolset, we apply this top-down design and implementation framework to real-world embedded systems, namely JPEG codec and Motion JPEG codec. Experimental results show that the developed tool remarkably decreases the design and verification time with modest performance penalty.

scholarly journals Teaching Reform and Innovation of Embedded System Development in the Context of Artificial Intelligence

2020 ◽  
Vol 2 (2) ◽  
pp. 18
Author(s):  
Chen Chen
Keyword(s):  
Artificial Intelligence ◽  
Embedded Systems ◽  
Embedded System ◽  
System Development ◽  
Rapid Development ◽  
Consumer Electronics ◽  
Computer Application ◽  
Application System ◽  
Teaching Reform ◽  
Software And Hardware

Embedded system is a special computer application system embedded in the object system. It is a combination of software and hardware. After decades of development, embedded systems have gradually entered many important industries such as industrial production, military, aerospace, transportation, wireless communications, and consumer electronics products, and their applications are extensive. The diversity of embedded systems has driven the rapid development of the embedded product market. In this paper, we analyze the teaching reform of embedded system development from the perspective of artificial intelligence. The sample models are integrated to help understand the proposed methodology. The numerical analysis proves the novelty.

Method of Realizing CNC Hand Wheel Function with CPLD

2013 ◽  
Vol 850-851 ◽  
pp. 608-611
Author(s):  
Hua Qun Zhan ◽  
Bin Xu ◽  
Juan Ying Zeng ◽  
Zai Song Yuan
Keyword(s):  
Hardware Design ◽  
Pulse Signal ◽  
Software Implementation ◽  
Circuit Board ◽  
Paper Briefly ◽  
Working Principle ◽  
Simulation Results

This paper briefly introduces the CNC hand wheel and analyzes the working principle of CNC hand wheel. Here make a circuit board based on the hardware design and software implementation. Simulation results were presented in this paper. Using this method can eliminate the interference of the hand wheel signal effectively and record the pulse signal of hand wheel accurately, and have achieved good results in FOXCONN.

Research of Development of Embedded Systems

2014 ◽  
Vol 539 ◽  
pp. 547-550
Author(s):  
Zi Li Jiang
Keyword(s):  
Embedded Systems ◽  
Embedded System ◽  
Computer Technology ◽  
Smart Devices ◽  
Database Applications ◽  
Application System ◽  
Database Technology ◽  
Software And Hardware ◽  
Near Future ◽  
Embedded Database

With embedded systems widely used and the continuous improvement of the user to the data processing and management needs, a variety of smart devices and database technology are tightly combined, this has got integrated attention. Embedded system is dedicated computer system that is application-centric, based on computer technology, software and hardware can be tailored to meet the stringent requirements of the application system, which strict with functionality, reliability, cost, size and power consumption. It is the product of the development of computer technology, now it has become an important part of the computer field. The embedded database will be in everywhere in the near future. Looking at the current international and domestic embedded database application, market has entered a stage of accelerated development based on embedded database applications.

The Embedded System Research for Multi-Definition Terminology

2013 ◽  
Vol 694-697 ◽  
pp. 2612-2615 ◽  
Author(s):  
Yan Ping Zhang ◽  
Li Min Liu
Keyword(s):  
Information Technology ◽  
Embedded Systems ◽  
Embedded System ◽  
System Research ◽  
Application System ◽  
The World ◽  
The Embedded System

Embedded system is an important and popular application system for information technology. The applications of embedded system are depended on embedded hardware and software. In fact, applications of embedded systems have changed life of people in the world. They can be found anywhere, and almost can be used in every field. Since there are multiple definitions for the terminology, few people exactly know the concept of an embedded system. In this paper, some important concepts and definitions of embedded system are discussed and analyzed. The research is helpful to understand the embedded systems and apply them better.

Compiler-Aided Run-Time Performance Speed-Up in Super-Scalar Processor

10.28945/3391 ◽  
2009 ◽  
Author(s):  
Moshe Pelleh
Keyword(s):  
Embedded Systems ◽  
Embedded System ◽  
General Purpose ◽  
Experimental Results ◽  
Medium Size ◽  
Organic System ◽  
Software Application ◽  
Organic Systems ◽  
Special Cases ◽  
Run Time

In our world, where most systems become embedded systems, the approach of designing embedded systems is still frequently similar to the approach of designing organic systems (or not embedded systems). An organic system, like a personal computer or a work station, must be able to run any task submitted to it at any time (with certain constrains depending on the machine). Consequently, it must have a sophisticated general purpose Operating System (OS) to schedule, dispatch, maintain and monitor the tasks and assist them in special cases (particularly communication and synchronization between them and with external devices). These OSs require an overhead on the memory, on the cache and on the run time. Moreover, generally they are task oriented rather than machine oriented; therefore the processor's throughput is penalized. On the other hand, an embedded system, like an Anti-lock Braking System (ABS), executes always the same software application. Frequently it is a small or medium size system, or made up of several such systems. Many small or medium size embedded systems, with limited number of tasks, can be scheduled by our proposed hardware architecture, based on the Motorola 500MHz MPC7410 processor, enhancing its throughput and avoiding the software OS overhead, complexity, maintenance and price. Encouraged by our experimental results, we shall develop a compiler to assist our method. In the meantime we will present here our proposal and the experimental results.

Algorithm for optimal allocation of limited resources based on the game iteration method

2019 ◽  
pp. 89-99
Author(s):  
V. Ya. Vilisov
Keyword(s):  
Optimal Control ◽  
Linear Programming ◽  
Embedded Systems ◽  
Iterative Method ◽  
High Speed ◽  
Optimal Allocation ◽  
Software Implementation ◽  
Limited Resources ◽  
Matrix Game ◽  
Acceptable Accuracy

The article proposes an algorithm for solving a linear programming problem (LPP) based on the use of its representation in the form of an antagonistic matrix game and the subsequent solution of the game by an iterative method. The algorithm is implemented as a computer program. The rate of convergence of the estimates of the solution to the actual value with the required accuracy has been studied. The software implementation shows a high speed of obtaining the LPP solution with acceptable accuracy in fractions or units of seconds. This allows the use algorithm in embedded systems for optimal control.

scholarly journals A Novel Rail-Network Hardware Simulator for Embedded System Programming

Electronics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 13
Author(s):  
Balaji M ◽  
Chandrasekaran M ◽  
Vaithiyanathan Dhandapani
Keyword(s):  
Embedded Systems ◽  
Embedded System ◽  
Real Time ◽  
Learning Outcomes ◽  
Real World ◽  
Time Constraints ◽  
Network Simulator ◽  
Practical Applications ◽  
Rail Network ◽  
Knowledge Enhancement

A Novel Rail-Network Hardware with simulation facilities is presented in this paper. The hardware is designed to facilitate the learning of application-oriented, logical, real-time programming in an embedded system environment. The platform enables the creation of multiple unique programming scenarios with variability in complexity without any hardware changes. Prior experimental hardware comes with static programming facilities that focus the students’ learning on hardware features and programming basics, leaving them ill-equipped to take up practical applications with more real-time constraints. This hardware complements and completes their learning to help them program real-world embedded systems. The hardware uses LEDs to simulate the movement of trains in a network. The network has train stations, intersections and parking slots where the train movements can be controlled by using a 16-bit Renesas RL78/G13 microcontroller. Additionally, simulating facilities are provided to enable the students to navigate the trains by manual controls using switches and indicators. This helps them get an easy understanding of train navigation functions before taking up programming. The students start with simple tasks and gradually progress to more complicated ones with real-time constraints, on their own. During training, students’ learning outcomes are evaluated by obtaining their feedback and conducting a test at the end to measure their knowledge acquisition during the training. Students’ Knowledge Enhancement Index is originated to measure the knowledge acquired by the students. It is observed that 87% of students have successfully enhanced their knowledge undergoing training with this rail-network simulator.

scholarly journals A Generalization Performance Study Using Deep Learning Networks in Embedded Systems

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1031
Author(s):  
Joseba Gorospe ◽  
Rubén Mulero ◽  
Olatz Arbelaitz ◽  
Javier Muguerza ◽  
Miguel Ángel Antón
Keyword(s):  
Deep Learning ◽  
Embedded Systems ◽  
Embedded System ◽  
General Purpose ◽  
Learning Networks ◽  
Performance Study ◽  
Learning Techniques ◽  
Wide Range ◽  
Learning Architectures

Deep learning techniques are being increasingly used in the scientific community as a consequence of the high computational capacity of current systems and the increase in the amount of data available as a result of the digitalisation of society in general and the industrial world in particular. In addition, the immersion of the field of edge computing, which focuses on integrating artificial intelligence as close as possible to the client, makes it possible to implement systems that act in real time without the need to transfer all of the data to centralised servers. The combination of these two concepts can lead to systems with the capacity to make correct decisions and act based on them immediately and in situ. Despite this, the low capacity of embedded systems greatly hinders this integration, so the possibility of being able to integrate them into a wide range of micro-controllers can be a great advantage. This paper contributes with the generation of an environment based on Mbed OS and TensorFlow Lite to be embedded in any general purpose embedded system, allowing the introduction of deep learning architectures. The experiments herein prove that the proposed system is competitive if compared to other commercial systems.

scholarly journals Singular Value Decomposition in Embedded Systems Based on ARM Cortex-M Architecture

Electronics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 34
Author(s):  
Michele Alessandrini ◽  
Giorgio Biagetti ◽  
Paolo Crippa ◽  
Laura Falaschetti ◽  
Lorenzo Manoni ◽  
...  
Keyword(s):  
Embedded Systems ◽  
Singular Value Decomposition ◽  
Embedded System ◽  
Mimo Systems ◽  
Singular Value ◽  
Measurement Unit ◽  
Comprehensive Treatment ◽  
Mathematical Tool ◽  
Value Decomposition ◽  
Speed Accuracy

Singular value decomposition (SVD) is a central mathematical tool for several emerging applications in embedded systems, such as multiple-input multiple-output (MIMO) systems, data analytics, sparse representation of signals. Since SVD algorithms reduce to solve an eigenvalue problem, that is computationally expensive, both specific hardware solutions and parallel implementations have been proposed to overcome this bottleneck. However, as those solutions require additional hardware resources that are not in general available in embedded systems, optimized algorithms are demanded in this context. The aim of this paper is to present an efficient implementation of the SVD algorithm on ARM Cortex-M. To this end, we proceed to (i) present a comprehensive treatment of the most common algorithms for SVD, providing a fairly complete and deep overview of these algorithms, with a common notation, (ii) implement them on an ARM Cortex-M4F microcontroller, in order to develop a library suitable for embedded systems without an operating system, (iii) find, through a comparative study of the proposed SVD algorithms, the best implementation suitable for a low-resource bare-metal embedded system, (iv) show a practical application to Kalman filtering of an inertial measurement unit (IMU), as an example of how SVD can improve the accuracy of existing algorithms and of its usefulness on a such low-resources system. All these contributions can be used as guidelines for embedded system designers. Regarding the second point, the chosen algorithms have been implemented on ARM Cortex-M4F microcontrollers with very limited hardware resources with respect to more advanced CPUs. Several experiments have been conducted to select which algorithms guarantee the best performance in terms of speed, accuracy and energy consumption.

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