{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":1,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":27,"n_cols":5,"rows_kept":27,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[2,4,2,5],[3,2,3,3],[5,2,5,3],[9,2,9,3],[10,2,10,3],[11,2,11,3],[12,2,12,3],[13,2,13,3],[14,2,14,3],[17,2,17,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNINA9910297366203321"]
[null,null,"Autore",null,"Parker Michael <1963-, >"]
[null,null,"Titolo",null,"Digital signal processing 101 : everything you need to know to get started / / Michael Parker"]
[null,null,"Pubbl/distr/stampa",null,"Oxford, United Kingdom ; ; Cambridge, MA : , : Newnes, , [2017]"]
[{"$nulls":4},"©2017"]
[null,null,"ISBN",null,"9780128114544"]
[{"$nulls":4},"0128114541"]
[{"$nulls":4},"9780128114537"]
[{"$nulls":4},"0128114533"]
[null,null,"Edizione",null,"[Second edition.]"]
[null,null,"Descrizione fisica",null,"1 online resource (417 pages) : colour illustrations"]
[null,null,"Disciplina",null,"621.3822 $2 23"]
[null,null,"Soggetti",null,"Signal processing - Digital techniques"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes index."]
[null,null,"Nota di contenuto",null,"Front Cover -- Digital Signal Processing 101 -- Digital Signal Processing 101: Everything you Need to Know to Get Started -- Copyright -- Contents -- Acknowledgments -- Introduction -- 1 - Numerical Representation -- 1.1 Integer Fixed Point Representation -- 1.2 Fractional Fixed Point Representation -- 1.3 Floating Point Representation -- 2 - Complex Numbers and Exponentials -- 2.1 Complex Addition and Subtraction -- 2.2 Complex Multiplication -- 2.3 Polar Representation -- 2.4 Complex Multiplication Using Polar Representation -- 2.5 Complex Conjugate -- 2.6 The Complex Exponential -- 2.7 Measuring Angles in Radians -- 3 - Sampling, Aliasing, and Quantization -- 3.1 Sampling Effects -- 3.2 Nyquist Sampling Rule -- 3.3 Quantization -- 3.4 Signal to Noise Ratio -- 4 - Frequency Response -- 4.1 Frequency Response and the Complex Exponential -- 4.2 Normalizing Frequency Response -- 4.3 Sweeping Across the Frequency Response -- 4.4 Example Frequency Responses -- 4.5 Linear Phase Response -- 4.6 Normalized Frequency Response Plots -- 5 - Finite Impulse Response (FIR) Filters -- 5.1 Finite Impulse Response Filter Construction -- 5.2 Computing Frequency Response -- 5.3 Computing Filter Coefficients -- 5.4 Effect of Number of Taps on Filter Response -- 6 - Windowing -- 6.1 Truncation of Coefficients -- 6.2 Tapering of Coefficients -- 6.3 Sample Coefficient Windows -- 7 - Decimation and Interpolation -- 7.1 Decimation -- 7.2 Interpolation -- "]
[{"$nulls":4},"7.3 Resampling by Noninteger Value -- 8 - Infinite Impulse Response (IIR) Filters -- 8.1 Infinite Impulse Response and Finite Impulse Response Filter Characteristic Comparison -- 8.2 Bilinear Transform -- 8.3 Frequency Prewarping -- 9 - Complex Modulation and Demodulation -- 9.1 Modulation Constellations -- 9.2 Modulated Signal Bandwidth -- 9.3 Pulse-Shaping Filter -- 9.4 Raised Cosine Filter."]
[{"$nulls":4},"10 - Discrete and Fast Fourier Transforms (DFT, FFT) -- 10.1 Discrete Fourier Transform and Inverse Discrete Fourier Transform Equations -- 10.2 First Discrete Fourier Transform Example -- 10.3 Second Discrete Fourier Transform Example -- 10.4 Third Discrete Fourier Transform Example -- 10.5 Fourth Discrete Fourier Transform Example -- 10.6 Fast Fourier Transform -- 10.7 Filtering Using the Fast Fourier Transform and Inverse Fast Fourier Transform -- 10.8 Bit Growth in Fast Fourier Transforms -- 10.9 Bit Reversal Addressing -- 11 - Digital Upconversion and Downconversion -- 11.1 Digital Upconversion -- 11.2 Digital Downconversion -- 11.3 Intermediate Frequency Subsampling -- 12 - Error-Correction Coding -- 12.1 Linear Block Encoding -- 12.2 Linear Block Decoding -- 12.3 Minimum Coding Distance -- 12.4 Convolutional Encoding -- 12.5 Viterbi Decoding -- 12.6 Soft Decision Decoding -- 12.7 Cyclic Redundancy Check -- 12.8 Shannon Capacity and Limit Theorems -- 13 - Matrix Inversion -- 13.1 Matrix Basics -- 13.2 Cholesky Decomposition -- 13.3 4×4 Cholesky Example -- 13.4 QR Decomposition -- 13.5 Gram-Schmidt Method -- 13.6 QR Decomposition Restructuring for Parallel Implementation -- 14 - Field-Oriented Motor Control -- 14.1 Magnetism Basics -- 14.2 AC Motor Basics -- 14.3 DC Motor Basics -- 14.4 Electronic Commutation -- 14.5 AC Induction Motor -- 14.6 Motor Control -- 14.7 Park and Clark Transforms -- 15 - Analog and Time Division Multiple Access Wireless Communications -- 15.1 Early Digital Innovations -- 15.2 Frequency Modulation -- 15.3 Digital Signal Processor -- 15.4 Digital Voice Phone Systems -- 15.5 Time Division Multiple Access Modulation and Demodulation -- 16 - CDMA Wireless Communications -- 16.1 Spread Spectrum Technology -- 16.2 Direct Sequence Spread Spectrum -- 16.3 Walsh Codes -- 16.4 Concept of Code Division Multiple Access."]
[{"$nulls":4},"16.5 Walsh Code Demodulation -- 16.6 Network Synchronization -- 16.7 RAKE Receiver -- 16.8 Pilot Pseudorandom Number Codes -- 16.9 Code Division Multiple Access Transmit Architecture -- 16.10 Variable Rate Vocoder -- 16.11 Soft Handoff -- 16.12 Uplink Modulation -- 16.13 Power Control -- 16.14 Higher Data Rates -- 16.15 Spectral Efficiency Considerations -- 16.16 Other Code Division Multiple Access Technologies -- 17 - Orthogonal Frequency Division Multiple Access Wireless Communications -- 17.1 WiMax and Long-Term Evolution -- 17.2 Orthogonal Frequency Division Multiple Access Advantages -- 17.3 Orthogonality of Periodic Signals -- 17.4 Frequency Spectrum of Orthogonal Subcarrier -- 17.5 Orthogonal Frequency Division Multiplexing Modulation -- 17.6 Intersymbol Interference and the Cyclic Prefix -- 17.7 Multiple Input and Multiple Output Equalization -- 17.8 Orthogonal Frequency Division Multiple Access System Considerations -- 17.9 Orthogonal Frequency Division Multiple Access Spectral Efficiency -- 17.10 Orthogonal Frequency Division Multiple Access Doppler Frequency Shift -- 17.11 Peak to Average Ratio -- 17.12 Crest Factor Reduction -- 17.13 Digital Predistortion -- 17.14 Remote Radio Head -- 18 - Radar Basics -- 18.1 Radar Frequency Bands -- 18.2 Radar Antennas -- 18.3 Radar Range Equation -- 18.4 Stealth Aircraft -- 18.5 Pulsed Radar Operation -- 18.6 Pulse Compression -- 18.7 Pulse Repetition Frequency -- 18.8 Detection Processing -- 19 - Pulse Doppler Radar -- 19.1 Doppler Effect -- 19.2 "]
[{"$nulls":4},"Pulsed Frequency Spectrum -- 19.3 Doppler Ambiguities -- 19.4 Radar Clutter -- 19.5 Pulse Repetition Frequency Trade-Offs -- 19.6 Target Tracking -- 20 - Automotive Radar -- 20.1 Frequency-Modulated Continuous-Wave Theory -- 20.2 Frequency-Modulated Continuous-Wave Range Detection -- 20.3 Frequency-Modulated Continuous-Wave Doppler Detection."]
[{"$nulls":4},"20.4 Frequency-Modulated Continuous-Wave Radar Link Budget -- 20.5 Frequency-Modulated Continuous-Wave Implementation Considerations -- 20.6 Frequency-Modulated Continuous-Wave Interference -- 20.7 Frequency-Modulated Continuous-Wave Beamforming -- 20.8 Frequency-Modulated Continuous-Wave Range-Doppler Processing -- 20.9 Frequency-Modulated Continuous-Wave Radar Front-End Processing -- 20.10 Frequency-Modulated Continuous-Wave Pulse-Doppler Processing -- 20.11 Frequency-Modulated Continuous-Wave Radar Back-End Processing -- 20.12 Noncoherent Antenna Magnitude Summation -- 20.13 Cell Averaging-Constant False Alarm Rate -- 20.14 Ordered Sort-Constant False Alarm Rate -- 20.15 Angle of Arrival Estimation -- 21 - Space Time Adaptive Processing (STAP) Radar -- 21.1 Space Time Adaptive Processing Radar Concept -- 21.2 Steering Vector -- 21.3 Interference Covariance Matrix -- 21.4 Space Time Adaptive Processing Optimal Filter -- 21.5 Space Time Adaptive Processing Radar Computational Requirements -- 22 - Synthetic Array Radar -- 22.1 Introduction -- 22.2 Synthetic Array Radar Resolution -- 22.3 Pulse Compression -- 22.4 Azimuth Resolution -- 22.5 Synthetic Array Radar Processing -- 22.6 Synthetic Array Radar Doppler Processing -- 22.7 Synthetic Array Radar Impairments -- 23 - Introduction to Video Processing -- 23.1 Color Spaces -- 23.2 Interlacing -- 23.3 Deinterlacing -- 23.4 Image Resolution and Bandwidth -- 23.5 Chroma Scaling -- 23.6 Image Scaling and Cropping -- 23.7 Alpha Blending and Compositing -- 23.8 Video Compression -- 23.9 Digital Video Interfaces -- 23.10 Legacy Analog Video Interfaces -- 24 - DCT, Entropy, Predictive Coding, and Quantization -- 24.1 Discrete Cosine Transform -- 24.2 Entropy -- 24.3 Huffman Coding -- 24.4 Markov Source -- 24.5 Predictive Coding -- 24.6 Differential Encoding -- 24.7 Lossless Compression -- 24.8 Quantization."]
[{"$nulls":4},"24.9 Decibels -- 25 - Image and Video Compression Fundamentals -- 25.1 Baseline JPEG -- 25.2 DC Scaling -- 25.3 Quantization Tables -- 25.4 Entropy Coding -- 25.5 JPEG Extensions -- 25.6 Video Compression Basics -- 25.7 Block Size -- 25.8 Motion Estimation -- 25.9 Frame Processing Order -- 25.10 Compressing I Frames -- 25.11 Compressing P Frames -- 25.12 Compressing B Frames -- 25.13 Rate Control and Buffering -- 25.14 Quantization Scale Factor -- 26 - Introduction to Machine Learning -- 26.1 Convolutional Neural Networks -- 26.2 Convolution Layer -- 26.3 Rectified Linear Unit Layer -- 26.4 Normalization Layer -- 26.5 Max-Pooling Layer -- 26.6 Fully Connected Layer -- 26.7 Training Computational Neural Networks -- 26.8 Winograd Transform -- 26.9 Convolutional Neural Network Numerical Precision Requirements -- 27 - Implementation Using Digital Signal Processors -- 27.1 Digital Signal Processing Processor Architectural Enhancements -- 27.1.1 Data I/O Bandwidth -- 27.1.2 Core Processing -- 27.1.3 Multiple Cores or Hardware Coprocessors -- 27.2 Scalability -- 27.3 Floating Point -- 27.4 Design Methodology -- 27.5 Managing Resources -- 27.6 Ecosystem -- 28 - Implementation Using FPGAs -- 28.1 FPGA Design Methodology -- 28.2 DSP Processor or FPGA Choice -- 28.3 Design Methodology Considerations -- 28.4 Dedicated Digital Signal Processing Circuit Blocks in FPGAs -- 28.4.1 Adjustable Precision Multipliers -- 28.4.2 Accumulator -- 28.4.3 "]
[{"$nulls":4},"Postadder (Subtractor) and Distributed Adder -- 28.4.4 Preadder (Subtractor) -- 28.4.5 Coefficient Storage -- 28.4.6 Barrel Shifter -- 28.4.7 Rounding and Saturation -- 28.4.8 Arithmetic Logic Unit Operations and Boolean Operations -- 28.4.9 Specialty Operations -- 28.4.10 Tco and Fmax -- 28.5 Floating Point Implementation Using FPGAs -- 28.6 Ecosystem -- 28.7 Future Trends -- 29 - Implementation With GPUs."]
[{"$nulls":4},"29.1 Characteristics of Graphics Processing Unit Architecture."]
[null,null,null,"Sommario/riassunto","Digital Signal Processing 101: Everything You Need to Know to Get Started provides a basic tutorial on digital signal processing (DSP). Beginning with discussions of numerical representation and complex numbers and exponentials, it goes on to explain difficult concepts such as sampling, aliasing, imaginary numbers, and frequency response. It does so using easy-to-understand examples with minimum mathematics. In addition, there is an overview of the DSP functions and implementation used in several DSP-intensive fields or applications, from error correction to CDMA mobile communication to airborne radar systems. This book has been updated to include the latest developments in Digital Signal Processing, and has eight new chapters on: Automotive Radar Signal Processing Space-Time Adaptive Processing Radar Field Orientated Motor Control Matrix Inversion algorithms GPUs for computing Machine Learning Entropy and Predictive Coding Video compression Features eight new chapters on Automotive Radar Signal Processing, Space-Time Adaptive Processing Radar, Field Orientated Motor Control, Matrix Inversion algorithms, GPUs for computing, Machine Learning, Entropy and Predictive Coding, and Video compression Provides clear examples and a non-mathematical approach to get you up to speed quickly Includes an overview of the DSP functions and implementation used in typical DSP-intensive applications, including error correction, CDMA mobile communication, and radar systems."]