This paper shows the development of a 1024-point
radix-4 FFT VHDL core for applications in hardware signal processing, targeting low-cost FPGA technologies. The developed core is targeted into a Xilinx廬 Spartan鈩?3 XC3S200 FPGA with the inclusion of a VGA display interface and an external 16-bit data acquisition system for performance evaluation purposes. Several tests were performed in order to verify FFT core functionality, besides the time performance analysis highlights the core advantages over commercially available DSPs and Pentium-based PCs. The core is compared with similar third party IP cores targeting resourceful FPGA technologies. The novelty of this work is to provide a lowcost, resource efficient core for spectrum analysis
applications.
200-MHz ARM920T Processor
• 16-kbyte Instruction Cache
• 16-kbyte Data Cache
• Linux® , Microsoft® Windows® CE-enabled MMU
• 100-MHz System Bus
• MaverickCrunch™ Math Engine
• Floating Point, Integer, and Signal Processing
Instructions
• Optimized for digital music compression and
decompression algorithms.
• Hardware interlocks allow in-line coding.
• MaverickKey™ IDs
• 32-bit Unique ID can be used for DRM-compliant
128-bit random ID.
• Integrated Peripheral Interfaces
• 32-bit SDRAM Interface
R. Lin and A.P. Petropulu, 揂 New Wireless Medium Access Protocol Based On Cooperation,擨EEE Trans. on Signal Processing, vol. 53, no. 12, pp. 4675-4684, December 2005. (MATLAB code).
R. Lin and A.P. Petropulu, 揂 New Wireless Medium Access Protocol Based On Cooperation,擨EEE Trans. on Signal Processing, vol. 53, no. 12, pp. 4675-4684, December 2005.
C Algorithms for Real-Time DSP
Chapter 4 covers the basic real-time filtering techniques which are the cornerstone of one-dimensional real-time digital signal processing.
C Algorithms for Real-Time DSP
Chapter 5 presents several real-time DSP applications, including speech compression music signal processing radar signal processing and adaptive signal processing techniques.
I. C. Wong, Z. Shen, J. G. Andrews, and B. L. Evans, ``A Low Complexity Algorithm for Proportional Resource Allocation in OFDMA Systems , Proc. IEEE Int. Work. Signal Processing Systems, 針對這篇文章給出的源代碼
Written for engineering and computer science students and practicing engineers, this book provides the fundamental applications and mathematical techniques of signal processing. Topics covered include programming in MATLAB, filters, networking, and parallel processing.
MATLAB is introduced and used to solve numerous examples in the book.
Companion software available
In addition, a set of MATLAB M-files is available on a CD bound in the book.
When trying to extract information from SAR images, we need to distinguish
two types of image property. The more important is where properties of the
scene (e.g., its dielectric constant, its geometry, its motion, etc.) produce effects
in the image measurements or examination of the image then can provide
information about the scene. The second is generated purely by the system
and the signal processing.
