Draft:Linear Convolution
| Submission declined on 23 June 2024 by Ldm1954 (talk). This submission is not adequately supported by reliable sources. Reliable sources are required so that information can be verified. If you need help with referencing, please see Referencing for beginners and Citing sources.
Where to get help
How to improve a draft
You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article. Improving your odds of a speedy review To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags. Editor resources
|  |
Comment: The topic is notable, but you have to put inline sources in, not just a list at the end. Every statement has to be verifiable by a source which is clearly evident to readers who know nothing.I also think you are limiting yourself too much to signal processing, it matters for anything that includes Fourier transforms such as diffraction and more. Ldm1954 (talk) 12:44, 23 June 2024 (UTC)
Linear convolution is a fundamental operation in signal processing and mathematics, essential for understanding the behavior of linear systems and processing signals in various applications such as communication systems, image processing, and audio processing. It involves combining two signals to produce a third signal that represents the mathematical convolution of the original signals.
Definition and Operation
[edit]Linear convolution is defined as the integral of the product of two functions, where one of the functions is reflected and shifted across the other function. Mathematically, the linear convolution y(t) of two signals x(t) and h(t) is given by:
In discrete-time signal processing, linear convolution is represented as the sum of the product of discrete samples of two signals. For discrete signals x[n] and h[n], the linear convolution y[n] is calculated as:
![{\displaystyle y[n]=\textstyle \sum _{k=-\infty }^{\infty }\displaystyle x[n]\cdot h[n-k]}](https://wikimedia.org/api/rest_v1/media/math/render/svg/acd197f130d70300254e9ad863fb40675247f13c)
Applications
[edit]Linear convolution finds applications in various fields:
- Digital Signal Processing (DSP): In DSP, linear convolution is used for filtering, system modeling, and signal analysis. For example, it is used in Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) filters.
- Communication Systems: In communication systems, linear convolution is used for channel modeling, equalization, and modulation/demodulation processes.
- Image Processing: In image processing, linear convolution is utilized for tasks such as blurring, edge detection, and image enhancement.
- Audio Processing: In audio processing, linear convolution is employed for effects processing, such as reverberation and echo generation.
See also
[edit]References
[edit]- ^ Oppenheim, Alan V.; Schafer, Ronald W. (2010). Discrete-time signal processing (3rd ed.). Upper Saddle River: Pearson. ISBN 978-0-13-198842-2.
- ^ Proakis, John G.; Manolakis, Dimitris G. (2011). Digital signal processing (4th ed.). New Delhi, India: Prentice Hall. ISBN 978-81-317-1000-5.
- ^ Gonzalez, Rafael C.; Woods, Richard E. (2018). Digital image processing (Fourth edition, india ed.). Uttar Pradesh: Pearson India. ISBN 978-93-5306-298-9.
- ^ Rabiner, Lawrence R.; Gold, Bernard (1975). Theory and application of digital signal processing. Englewood Cliffs, N.J: Prentice-Hall. ISBN 978-0-13-914101-0.