Loading presentation...

Present Remotely

Send the link below via email or IM

Copy

Present to your audience

Start remote presentation

  • Invited audience members will follow you as you navigate and present
  • People invited to a presentation do not need a Prezi account
  • This link expires 10 minutes after you close the presentation
  • A maximum of 30 users can follow your presentation
  • Learn more about this feature in our knowledge base article

Do you really want to delete this prezi?

Neither you, nor the coeditors you shared it with will be able to recover it again.

DeleteCancel

Make your likes visible on Facebook?

Connect your Facebook account to Prezi and let your likes appear on your timeline.
You can change this under Settings & Account at any time.

No, thanks

PC-based digital signal processor

Our graduation project which record a signal and make an auto detect for any DC noise and filter it.
by

odai alsgier

on 23 May 2013

Comments (0)

Please log in to add your comment.

Report abuse

Transcript of PC-based digital signal processor

PC-based digital signal processor project overview presentation is ended
thankfully
thanks for listening :))) to design a digital signal processing system with a built -in analog interface that allows signal analysis & processing process Fourier Transform
- localized in frequency only
–Time complexity: O(n2)
–Sinusoid with frequencies in arithmetic progression
Short-time Fourier Transform
–Sinusoid times Gaussian
–Time complexity: O(N)
–Fixed-width Gaussian “window”
•Wavelet
- localized in both time and frequency
–Basis has constant shape independent of scale
–Time complexity: O(N). analysis our graduation project proposal

http://goo.gl/45KkI

http://goo.gl/zn0gp

http://en.wikipedia.org/wiki/Wavelet#Comparisons_with_Fourier_transform_.28continuous-time.29 References for this presentation: created by: odai mohammad alsgier
mohammad ibrahim assadeq
mohammad faroq hamdan Tools used: Computer [includes ADC, DAC, microphone]
Useful programs like Matlab, C# which includes the Mitov audiolab library
Methods of DSP like discrete Fourier transform, wavelet transform, spectrum analysis & processing problems targeted Automatical noise filtration for data transmission technology
Signal analysis in time , frequency and transform domains
Electrical engineering- control the level of total harmonics section1: recording a signal... The first section in this project is to record a signal with a specific period or with an open time.
The signal could be .mp3 or .wav file format.
The frequency can be changed due to the usage of the signal we want(as written in the documentation)
the next video shows an example: Auto filtration of any () noise... The first option offered by our project is to make an auto detect for any noise and filter it automatically
all what you have to do is to select the signal you want to filter and to determine the path for filtered signal then press (filter now) button.
when the program ends the filtration a message pops to the user Wavelet, spectrum and Fourier for any mp3 signal for any mp3 signal you can perform Fourier transform or wavelet transform or do the spectrum analysis for it.
only specify the signal you want and then press on the button next to it. wavelet transform
of the test signal... spectrum analysis... Fourier transform The output of the transformations: section2: processing a signal Introduction: Fourier Transform (Sum of harmonics): Any periodic wave can be turned into a sum of different amplitude sine waves
Any periodic wave can be decomposed in a Fourier series
Fourier Transform is a function can be described by a summation of waves with different amplitudes and phases. Short Time Fourier Transform(Windowed F.T.) Segmenting the signal into narrow time intervals (i.e., narrow enough to be considered stationary).
Take the Fourier transform of each segment.
What shape? Rectangular, Gaussian, Elliptic? Wavelet Transform Wavelets are functions defined over a finite interval and having an average value of zero.
Wavelet Analysis is based on an short duration wavelet of a specific center frequency
The basic idea of the wavelet transform is to represent any arbitrary function (t) as a superposition of a set of such wavelets or basis functions. The signal wave Form before & after filtration: Before Filtration wave form After filtration wave form
Full transcript