This course provides a foundation for Digital Signal Processing (DSP) techniques for Xilinx FPGAs.
The emphasis is on:
The emphasis is on:
- Reviewing basic binary number theory, mathematics, and the essential features within the FPGA that are important to signal processing
- Exploring a variety of filter techniques with a focus on optimal implementation in Xilinx devices and continues with an examination of FFTs, video, and image processing
- Introducing Xilinx cores and IP that are relevant to signal processing
Release dateAugust 2012
Training duration2 days
PriceUSD 1600 or 16 Training Credits
Course Part NumberDSP-ESS-ILT
Who Should Attend?Engineers and designers who have an interest in developing products that use digital signal processing.
- A fundamental understanding of digital signal processing theory, including an understanding of the following principles
- Sample rates
- Finite Impulse Response (FIR) and Infinite Impulse Response (IIR)
- Oscillators and mixers
- Fast Fourier Transform (FFT) algorithm
- Architecture: 7 series FPGAs
- Demo board: None
Skills gainedAfter completing this comprehensive training, you will have the necessary skills to:
- Describe the advantages of using FPGAs over traditional processors for DSP designs
- Utilize fixed point binary arithmetic and identify how to use this knowledge to create efficient designs in FPGAs
- Recognize how both the CLB slices in FPGAs and the more advanced DSP48s are used to implement DSP algorithms
- Explain the dataflow through the device and how to use distributed memory, block RAM, registers, and SRLs to properly implement these designs
- Construct different FIR filter and FFT implementations and how to optimize these implementations in the FPGA
- Explain the algorithms for video and imaging systems and their implementations in FPGAs
- Back to Basics
- FPGA Math
- Exercise 1: Signed Number Conversion, Quantization and Rounding, Adders, Subtractors, and Accumulation
- Shift Registers, RAM, and Applications
- Exercise 2: SRL32E and RAM Estimation and Concatenation
- FIR Filter
- Exercise 3: Filter Implementation, Resource and Performance Estimation
- Advanced Filter Techniques
- Exercise 4: Filter Implementations, Resource and Performance Estimation
- Fast Fourier Transform
- Exercise 5: FFT Implementation, Resource and Performance Estimation
- Video and Imaging
- Where Do We Go From Here?
- Demonstration: System Generator and the CORE Generator Tool with a DSP-Targeted Reference Design
- Where Can I Learn More?
- Exercise 1: Signed Number Conversion, Quantization and Rounding, Adders, Subtractors, and Accumulation - Learn how to estimate device resource utilization for basic math functions. Compare different methodologies for implementing functions.
- Exercise 2: SRL32E and RAM Estimation and Concatenation - Learn how to optimize memory and storage in Xilinx FPGAs.
- Exercise 3: Filter Implementation, Resource and Performance Estimation - Learn how and when to use various implementation strategies for optimal filter implementation.
- Exercise 4: Filter Implementations, Resource and Performance Estimation - Advanced filter topologies are studied. Architect multichannel and multirate filters using various methods. Implementation strategies will be discussed and optimal methods used.
- Exercise 5: FFT Implementation, Resource and Performance Estimation - Select correct parameters for FFT implementations to meet design targets. Resource estimation will be studied and trade-offs with performance examined through implementation examples.
- Demonstration: System Generator and the CORE Generator Tool with a DSP-Targeted Reference Design - Introduces DSP-targeted hardware boards and software tools. Witness the power, ease of use, and design efficiency of Xilinx DSP tools and IP. Reinforce the concepts studied in the course material and exercises.