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Synthesizer.Dimensional.RateAmplitude.Analysis | Portability | requires multi-parameter type classes | Stability | provisional | Maintainer | synthesizer@henning-thielemann.de |
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Description |
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Synopsis |
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centroid :: (C q, C u, C v) => T u q (S v y) q -> T u q | | length :: (C t, C u, C v) => T u t (S v y) yv -> T u t | | normMaximum :: (C y, C u, C v) => T u t (S v y) y -> T v y | | normVectorMaximum :: (C q yv, Ord q, C u, C v) => T u q (S v q) yv -> T v q | | normEuclideanSqr :: (C q, C u, C v) => T u q (S v q) q -> T (Mul u (Sqr v)) q | | normVectorEuclideanSqr :: (C q yv, C q, C u, C v) => T u q (S v q) yv -> T (Mul u (Sqr v)) q | | normSum :: (C q, C q, C u, C v) => T u q (S v q) q -> T (Mul u v) q | | normVectorSum :: (C q yv, C q, C u, C v) => T u q (S v q) yv -> T (Mul u v) q | | normMaximumProc :: (C y, C u, C v) => T s u y (R s v y y -> T v y) | | normVectorMaximumProc :: (C y yv, Ord y, C u, C v) => T s u y (R s v y yv -> T v y) | | normEuclideanSqrProc :: (C q, C u, C v) => T s u q (R s v q q -> T (Mul u (Sqr v)) q) | | normVectorEuclideanSqrProc :: (C y yv, C y, C u, C v) => T s u y (R s v y yv -> T (Mul u (Sqr v)) y) | | normSumProc :: (C q, C q, C u, C v) => T s u q (R s v q q -> T (Mul u v) q) | | normVectorSumProc :: (C y yv, C y, C u, C v) => T s u y (R s v y yv -> T (Mul u v) y) | | histogram :: (C q, C u, C v) => T u q (S v q) q -> T s v q (Int, R s (DimensionGradient v u) q q) | | zeros :: (Ord q, C q, C u, C v) => T s u q (R s v q q -> R s (Recip u) q q) | | toFrequencySpectrum :: (C q, C u, C v) => T u q (D v q (T T)) (T q) -> T (Recip u) q (D (Mul u v) q (T T)) (T q) | | fromFrequencySpectrum :: (C q, C u, C v) => T (Recip u) q (D (Mul u v) q (T T)) (T q) -> T u q (D v q (T T)) (T q) |
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Documentation |
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centroid :: (C q, C u, C v) => T u q (S v y) q -> T u q | Source |
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length :: (C t, C u, C v) => T u t (S v y) yv -> T u t | Source |
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normMaximum :: (C y, C u, C v) => T u t (S v y) y -> T v y | Source |
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Manhattan norm.
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normVectorMaximum :: (C q yv, Ord q, C u, C v) => T u q (S v q) yv -> T v q | Source |
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Manhattan norm.
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Square of energy norm.
Could also be called variance.
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normVectorEuclideanSqr :: (C q yv, C q, C u, C v) => T u q (S v q) yv -> T (Mul u (Sqr v)) q | Source |
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Energy norm.
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Sum norm.
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normVectorSum :: (C q yv, C q, C u, C v) => T u q (S v q) yv -> T (Mul u v) q | Source |
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Sum norm.
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normMaximumProc :: (C y, C u, C v) => T s u y (R s v y y -> T v y) | Source |
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Manhattan norm.
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normVectorMaximumProc :: (C y yv, Ord y, C u, C v) => T s u y (R s v y yv -> T v y) | Source |
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Manhattan norm.
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normEuclideanSqrProc :: (C q, C u, C v) => T s u q (R s v q q -> T (Mul u (Sqr v)) q) | Source |
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Square of energy norm.
Could also be called variance.
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normVectorEuclideanSqrProc :: (C y yv, C y, C u, C v) => T s u y (R s v y yv -> T (Mul u (Sqr v)) y) | Source |
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Energy norm.
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normSumProc :: (C q, C q, C u, C v) => T s u q (R s v q q -> T (Mul u v) q) | Source |
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Sum norm.
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normVectorSumProc :: (C y yv, C y, C u, C v) => T s u y (R s v y yv -> T (Mul u v) y) | Source |
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Sum norm.
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Detects zeros (sign changes) in a signal.
This can be used as a simple measure of the portion
of high frequencies or noise in the signal.
The result has a frequency as amplitude.
If you smooth it, you will get a curve that represents a frequency progress.
It ca be used as voiced/unvoiced detector in a vocoder.
The result will be one value shorter than the input.
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Fourier analysis
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Fourier synthesis
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Produced by Haddock version 2.4.2 |