Digital Signal Processing Using the ARM Cortex M4

Häftad, Engelska, 2015

AvDonald S. Reay,Donald S. (Heriot-Watt University) Reay

1 269 kr

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Features inexpensive ARM® Cortex®-M4 microcontroller development systems available from Texas Instruments and STMicroelectronics.This book presents a hands-on approach to teaching Digital Signal Processing (DSP) with real-time examples using the ARM® Cortex®-M4 32-bit microprocessor. Real-time examples using analog input and output signals are provided, giving visible (using an oscilloscope) and audible (using a speaker or headphones) results. Signal generators and/or audio sources, e.g. iPods, can be used to provide experimental input signals. The text also covers the fundamental concepts of digital signal processing such as analog-to-digital and digital-to-analog conversion, FIR and IIR filtering, Fourier transforms, and adaptive filtering.Digital Signal Processing Using the ARM® Cortex®-M4: Uses a large number of simple example programs illustrating DSP concepts in real-time, in an electrical engineering laboratory settingIncludes examples for both STM32F407 Discovery and the TM4C123 Launchpad, using Keil MDK-ARM, on a companion websiteExample programs for the TM4C123 Launchpad using Code Composer Studio version 6 available on companion websiteDigital Signal Processing Using the ARM® Cortex®-M4 serves as a teaching aid for university professors wishing to teach DSP using laboratory experiments, and for students or engineers wishing to study DSP using the inexpensive ARM® Cortex®-M4.

Produktinformation

Utgivningsdatum2015-10-30
Mått158 x 236 x 20 mm
Vikt463 g
FormatHäftad
SpråkEngelska
Antal sidor320
FörlagJohn Wiley & Sons Inc
ISBN9781118859049

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DONALD S. REAY is lecturer in electrical engineering at Heriot-Watt University in Edinburgh, Scotland. He has also taught hands-on DSP, on a number of occasions, as a visiting lecturer at Zhejiang University in Hangzhou, China. He co-authored Digital Signal Processing and Applications with the TMS320C6713 and TMS320C6416 DSK, Second Edition (Wiley, 2008) with Rulph Chassaing, and is the author of Digital Signal Processing and Applications with the OMAP-L138 eXperimenter (Wiley, 2012).

Preface xi1 ARM® CORTEX® - M4 Development Systems 11.1 Introduction 11.1.1 Audio Interfaces 21.1.2 Texas Instruments TM4C123 LaunchPad and STM32F407 Discovery Development Kits 21.1.3 Hardware and Software Tools 6Reference 72 Analog Input and Output 92.1 Introduction 92.1.1 Sampling, Reconstruction, and Aliasing 92.2 TLV320AIC3104 (AIC3104) Stereo Codec for Audio Input and Output 102.3 WM5102 Audio Hub Codec for Audio Input and Output 122.4 Programming Examples 122.5 Real-Time Input and Output Using Polling, Interrupts, and Direct Memory Access (DMA) 122.5.1 I2S Emulation on the TM4C123 152.5.2 Program Operation 152.5.3 Running the Program 162.5.4 Changing the Input Connection to LINE IN 162.5.5 Changing the Sampling Frequency 162.5.6 Using the Digital MEMS Microphone on the Wolfson Audio Card 202.5.7 Running the Program 212.5.8 Running the Program 232.5.9 DMA in the TM4C123 Processor 262.5.10 Running the Program 302.5.11 Monitoring Program Execution 302.5.12 Measuring the Delay Introduced by DMA-Based I/O 302.5.13 DMA in the STM32F407 Processor 342.5.14 Running the Program 352.5.15 Measuring the Delay Introduced by DMA-Based I/O 352.5.16 Running the Program 462.6 Real-Time Waveform Generation 462.6.1 Running the Program 492.6.2 Out-of-Band Noise in the Output of the AIC3104 Codec (tm4c123_sine48_intr.c). 492.6.3 Running the Program 532.6.4 Running the Program 622.6.5 Running the Program 692.7 Identifying the Frequency Response of the DAC Using Pseudorandom Noise 702.7.1 Programmable De-Emphasis in the AIC3104 Codec 722.7.2 Programmable Digital Effects Filters in the AIC3104 Codec 722.8 Aliasing 782.8.1 Running the Program 832.9 Identifying the Frequency Response of the DAC Using An Adaptive Filter 832.9.1 Running the Program 842.10 Analog Output Using the STM32F407’S 12-BIT DAC 91References 963 Finite Impulse Response Filters 973.1 Introduction to Digital Filters 973.1.1 The FIR Filter 973.1.2 Introduction to the z-Transform 993.1.3 Definition of the z-Transform 1003.1.4 Properties of the z-Transform 1083.1.5 z-Transfer Functions 1113.1.6 Mapping from the s-Plane to the z-Plane 1113.1.7 Difference Equations 1123.1.8 Frequency Response and the z-Transform 1133.1.9 The Inverse z-Transform 1143.2 Ideal Filter Response Classifications: LP, HP, BP, BS 1143.2.1 Window Method of FIR Filter Design 1143.2.2 Window Functions 1163.2.3 Design of Ideal High-Pass Band-Pass and Band-Stop FIR Filters Using the Window Method 1203.3 Programming Examples 1233.3.1 Altering the Coefficients of the Moving Average Filter 1323.3.2 Generating FIR Filter Coefficient Header Files Using MATLAB 1374 Infinite Impulse Response Filters 1634.1 Introduction 1634.2 IIR Filter Structures 1644.2.1 Direct Form I Structure 1644.2.2 Direct Form II Structure 1654.2.3 Direct Form II Transpose 1664.2.4 Cascade Structure 1684.2.5 Parallel Form Structure 1694.3 Impulse Invariance 1714.4 Bilinear Transformation 1714.4.1 Bilinear Transform Design Procedure 1724.5 Programming Examples 1734.5.1 Design of a Simple IIR Low-Pass Filter 173Reference 2165 Fast Fourier Transform 2175.1 Introduction 2175.2 Development of the FFT Algorithm with RADIX-2 2185.3 Decimation-in-Frequency FFT Algorithm with RADIX-2 2195.4 Decimation-in-Time FFT Algorithm with RADIX-2 2225.4.1 Reordered Sequences in the Radix-2 FFT and Bit-Reversed Addressing 2245.5 Decimation-in-Frequency FFT Algorithm with RADIX-4 2265.6 Inverse Fast Fourier Transform 2275.7 Programming Examples 2285.7.1 Twiddle Factors 2335.8 Frame- or Block-Based Programming 2395.8.1 Running the Program 2425.8.2 Spectral Leakage 2445.9 Fast Convolution 2525.9.1 Running the Program 2565.9.2 Execution Time of Fast Convolution Method of FIR Filter Implementation 256Reference 2616 Adaptive Filters 2636.1 Introduction 2636.2 Adaptive Filter Configurations 2646.2.1 Adaptive Prediction 2646.2.2 System Identification or Direct Modeling 2656.2.3 Noise Cancellation 2656.2.4 Equalization 2666.3 Performance Function 2676.3.1 Visualizing the Performance Function 2696.4 Searching for the Minimum 2706.5 Least Mean Squares Algorithm 2706.5.1 LMS Variants 2726.5.2 Normalized LMS Algorithm 2726.6 Programming Examples 2736.6.1 Using CMSIS DSP Function arm_lms_f32() 280Index 299