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Designing Embedded Systems With 32 Bit Pic Microcontrollers And Mikroc

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Designing Embedded Systems with 32 Bit PIC Microcontrollers and MikroC

Designing Embedded Systems with 32 Bit PIC Microcontrollers and MikroC Book
Author : Dogan Ibrahim
Publisher : Newnes
Release : 2013-08-22
ISBN : 0080981992
Language : En, Es, Fr & De

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Book Description :

The new generation of 32-bit PIC microcontrollers can be used to solve the increasingly complex embedded system design challenges faced by engineers today. This book teaches the basics of 32-bit C programming, including an introduction to the PIC 32-bit C compiler. It includes a full description of the architecture of 32-bit PICs and their applications, along with coverage of the relevant development and debugging tools. Through a series of fully realized example projects, Dogan Ibrahim demonstrates how engineers can harness the power of this new technology to optimize their embedded designs. With this book you will learn: The advantages of 32-bit PICs The basics of 32-bit PIC programming The detail of the architecture of 32-bit PICs How to interpret the Microchip data sheets and draw out their key points How to use the built-in peripheral interface devices, including SD cards, CAN and USB interfacing How to use 32-bit debugging tools such as the ICD3 in-circuit debugger, mikroCD in-circuit debugger, and Real Ice emulator Helps engineers to get up and running quickly with full coverage of architecture, programming and development tools Logical, application-oriented structure, progressing through a project development cycle from basic operation to real-world applications Includes practical working examples with block diagrams, circuit diagrams, flowcharts, full software listings an in-depth description of each operation

ARM Based Microcontroller Multitasking Projects

ARM Based Microcontroller Multitasking Projects Book
Author : Dogan Ibrahim
Publisher : Newnes
Release : 2020-05-14
ISBN : 0128226315
Language : En, Es, Fr & De

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Book Description :

Most microcontroller-based applications nowadays are large, complex, and may require several tasks to share the MCU in multitasking applications. Most modern high-speed microcontrollers support multitasking kernels with sophisticated scheduling algorithms so that many complex tasks can be executed on a priority basis. ARM-based Microcontroller Multitasking Projects: Using the FreeRTOS Multitasking Kernel explains how to multitask ARM Cortex microcontrollers using the FreeRTOS multitasking kernel. The book describes in detail the features of multitasking operating systems such as scheduling, priorities, mailboxes, event flags, semaphores etc. before going onto present the highly popular FreeRTOS multitasking kernel. Practical working real-time projects using the highly popular Clicker 2 for STM32 development board (which can easily be transferred to other boards) together with FreeRTOS are an essential feature of this book. Projects include: LEDs flashing at different rates; Refreshing of 7-segment LEDs; Mobile robot where different sensors are controlled by different tasks; Multiple servo motors being controlled independently; Multitasking IoT project; Temperature controller with independent keyboard entry; Random number generator with 3 tasks: live, generator, display; home alarm system; car park management system, and many more. Explains the basic concepts of multitasking Demonstrates how to create small multitasking programs Explains how to install and use the FreeRTOS on an ARM Cortex processor Presents structured real-world projects that enables the reader to create their own

Mission Oriented Sensor Networks and Systems Art and Science

Mission Oriented Sensor Networks and Systems  Art and Science Book
Author : Habib M. Ammari
Publisher : Springer Nature
Release : 2019-09-18
ISBN : 3319923846
Language : En, Es, Fr & De

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Book Description :

This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.