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It is well known that the Fourier Transform (FT) has currently a key role in signal processing applications.

The FT is useful for frequency domain analysis of a signal, i.e. it transposes a signal from time domain into

frequency domain. Many application ranging from telecommunication, electric energy distribution systems, fail

prevention analysis and general signal processing use this transform as a tool for coding/decoding or spectrum

analysis of a signal. Because of the complexity of the processing algorithm of FT and its importance in signal

analysis, many people have been working on methods and application specific processor architecture for improving

the computation performance. To get that performance improvement, efforts have been done in two directions

mainly. One related to the algorithmic point of view[1,2,3], and the other based on ASIP architecture[2,4,5,6]. The

last one was pushed by VLSI technology evolution.

In this work, we present an architecture of a processor to perform FT analysis employing a datapath with

bit-serial and digit-serial integer operation. The objective of this work was get an area efficient architecture that

could be used as a co-processor with built in all resources necessary for an embedded application. Also, we guide our

design to have a simple input / output interface. The main difference between the architecture presented here and the

others rely on the usage of a datapath bit and digit serial oriented to process each butterfly highly parallel.

This paper is organized as follows. Section 2 provides a review of FT computation. Section 3 discusses the

proposed architecture, while section 4 presents some results, followed by conclusions and future work.

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Related questions

What are there advantages and where are there used fft?

because they have a high speed compared to fft


What are there advantages and where are there used?

FFT reduces the computation since no. of complex multiplications required in FFT are N/2(log2N). FFT is used to compute discrete Fourier transform.


How do you plot frequency spectrum using fft function in MATLAB?

To plot the frequency spectrum using the fft function in MATLAB, first compute the one-dimensional discrete Fourier transform using fft, provide the data series as an input. Then use the abs() function to get the magnitude spectrum, and plot the result using the plot() function, with the frequency domain on the x-axis and the magnitude spectrum on the y-axis.


Need of fft?

FT is needed for spectrum analysis, FFT is fast FT meaning it is used to obtain spectrum of a signal quickly, the FFT algorithm inherently is fast algorithm than the conventional FT algorithm


What is the need of FFT?

There's no need for it.


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Zoom FFT is a diagnostic tool for the detection of blood clots and other diseases. It is less costly than other techniques. Zoom FFT uses a low frequency to measure blood flow in order to find clots. A transmitter passes an ultrasonic wave through the blood vessels. A reflected signal is passed to a DSP processor. (This is similar to the Doppler technique.) The process is achieved with one DSP chip in order to keep the costs lower.


Why FFT is faster than DFT?

FFT is faster than DFT because no. of complex multiplication in DFT is N^2 while in FFT no. of complex multiplications are N/2(log2N). for example if N=8 no. of complex multiplications required in DFT are 64. while no. of complex multiplications required in FFT are 12 thus reduces computation time.


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How do you plot FFT in simulink?

FFT is the frequency domain representation. In can be shown in Simulink with blocks. These blocks graphically show the domain or x value plotted against the frequency or y value.