Month: September 2016

THE EMBEDDED LEARNING SCHOOL

A Guide to the Internet of Things (IoT)

The Big Data Bang The “Internet of Things” is exploding. It is made up of billions of “smart” devices—from minuscule chips to mammoth machines—that use wireless technology to talk to each other (and to us). Our IoT world is growing at a breathtaking pace, from 2 billion objects in 2006 to a projected 200 billion…
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CACHE MEMORY PRINCIPLES

Cache memory is intended to give memory speed approaching that of the fastest memories available, and at the same time provide a large memory size at the price of less expensive types of semiconductor memories. The concept is illustrated in Figure (a) below. There is a relatively large and slow main memory together with a…
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Next-Gen Sensors Make Golf Clubs, Tennis Rackets, and Baseball Bats Smarter Than Ever

Sensor fusion and integrated MEMS are essential tools for today’s athletes     A golfer stands in the dreaded sand trap, carefully considering how to balance his weight as he eyes the ball. He takes a few practice swings. If he swings too deeply, he’ll hit the ground and lose another stroke. It’s a tough shot, but…
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Setting up Keil for Your First LED Blinking Program on STM32F7 Discovery Board

The STM32F745xx and STM32F746xx devices are based on the high-performance ARM®Cortex®-M7 32-bit RISC core operating at up to 216 MHz frequency. The Cortex®-M7 core features a single floating point unit (SFPU) precision which supports all ARM®single-precision data-processing instructions and data types. It also implements a full set of DSP instructions and a memory protection unit…
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LM35 Temperature Sensor and LCD Display interfacing with AVR ATmega32

In this project, we are going to design a circuit for measuring temperature. This circuit is developed using “LM35”, a linear voltage sensor. Temperature is usually measured in “Centigrade” or “Fahrenheit”. “LM35” sensor provides the output based on the scale of centigrade.

System Identification using Adaptive LMS and Normalized LMS Filter in MATLAB

There are four major types of adaptive filtering configurations; adaptive system identification, adaptive noise cancellation, adaptive linear prediction, and adaptive inverse system. All of the above systems are similar in the implementation of the algorithm but different in system configuration. All 4 systems have the same general parts; an input x(n), a desired result d(n), an…
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STM32 Nucleo Board Programming – UART printf Coding in Keil using STM32CubeMx

NUCLEO-F401RE – STM32 Nucleo-64 development board with STM32F401RE MCU, supports Arduino and ST morpho connectivity – STMicroelectronics The STM32 Nucleo board provides an affordable and flexible way for users to try out new ideas and build prototypes with any STM32 microcontroller line, choosing from the various combinations of performance, power consumption and features. The Arduino™…
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Creating a new AVR Assembly Project in AVR Studio 6

https://www.youtube.com/watch?v=_kChddN76S8 This AVR tutorial will go through the steps to create an AVR Assembly project in AVR Studio 6. This tutorial assume that you have already install AVR Studio 6 or above on you computer Step 1: To create an assembly project first start AVR Studio 6 by going to the start menu on your…
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Find the Periodicity of Noisy Data using Autocorrelation method in MATLAB

Autocorrelation (short ACF, autocorrelation function) is a cross-correlation of a signal with itself. By correlating a signal with itself, repetitive patterns will stand out and make it much easier to see. The (discrete) autocorrelation of a signal x is defined by the following simple equation. The entire signal x is shifted by an offset j and then multiplied by the original signal. This…
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Moving Average FIR Filter in MATLAB

As the name implies, the moving average filter operates by averaging a number of points from the input signal to produce each point in the output signal. In equation form, this is written: Where x[ ] is the input signal, y[ ] is the output signal, and M is the number of points in the…
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