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Everything about Multidimensional discrete convolution
Mathematical operation in signal processing
In signal processing, multidimensional discrete convolution refers to the mathematical operation between two functions f and g on an n-dimensional lattice that produces a third function, also of n-dimensions. Multidimensional discrete convolution is the discrete analog of the multidimensional convolution of functions on Euclidean space. It is also a special case of convolution on groups when the group is the group of n-tuples of integers. Wikipedia →
🧠Start here: a 6-step reading path
- Read the overview: Multidimensional discrete convolutionA 5-minute orientation
- Pick up a classic book: Fast algorithms for signal processingThe most-reprinted book on the subject
- Read the landmark paper: Symmetric convolution of asymmetric multidimensional sequences using discrete trigonometric transformsCited 9 times
- Go sideways: Discrete Hartley transformA closely related topic
- Go sideways: Discrete Fourier transformA closely related topic
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No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
đź“š Books worth reading
Fast algorithms for signal processingRichard E. Blahut · 2010
Multiplicative Complexity, Convolution, and the DFTMichael T. Heideman · 1988
Algorithm Design and ApplicationsMichael T. Goodrich, Roberto Tamassia · 2014
Digital Signal Processing · 2006
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
đź”— Related topics
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