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.
Fast Fourier Transform power point
The rectangular window introduces broadening of any frequency components [`smearing鈥? and sidelobesthat may overlap with other frequency components [`leakage鈥?.
鈥he effect improves as Nincreases
鈥owever, the rectangle window has poor properties and better choices of wncan lead to better spectral properties [less leakage, in particular] 鈥搃.e. instead of just truncating the summation, we can pre-multiply by a suitable window function wnthat has better frequency domain properties.
鈥ore on window design in the filter design section of the course
ITU-T G.729 Annex C+ - Reference C code for floating point
implementation of G.729 at 6.4/8/11.8 kbit/s with DTX functionality
(integration of Annexes B, D and E)
A Convex Hull is the smallest convex polygon that contains every point of the set S. A polygon P is convex if and only if, for any two points A and B inside the polygon, the line segment AB is inside P.
One way to visualize a convex hull is to put a "rubber band" around all the points, and let it wrap as tight as it can. The resultant polygon is a convex hull.
