Convolution. Zithergeist features a Convolution module to further colour and sculpt the sound of the instruments. Very briefly, convolution is a sophisticated mathematical process that allows you to filter a sound within another one. It's very frequently used to carefully reproduce the acoustic reverberation of real environments (rooms, halls etc) or even hardware reverb units (spring reverbs, digital reverbs etc). However, by experimenting with the choice of the audio files used as IRs (Impulse Responses), it is possible to get creative with sound design and produce unusual effects. The convolution samples (IRs) used in Zithergeist fall under this umbrella: you can experiment by selecting more than 120 experimental samples, which have been divided in two categories, texture and rhythm. Moreover, you can use the convolution samples even outside of Kontakt, loading them in your favourite convolution reverb (please see Section 3). Predelay Controls the pre-delay of the convolution effect Size Controls the 'size' of the convolution sample; in Kontakt, this corresponds to a non-linear stretching of the sampler HPF Controls the high-pass filter applied to the convolution sample LPF Controls the low-pass filter applied to the convolution sample Wet Controls the amount of the applied Reverb Texture switch Shows the textural convolution samples within the menu Rhythm switch Shows the rhythmical convolution samples within the menu Tip 1: try to adjust the Size on a rhythmical convolution sample to obtain interesting subtle rhythms Tip 2: be careful with the Wet knob! Convolution could create unpleasant resonances at high volume. When exploring the convolution samples, always start with low Wet and increase the value little by little. We also recommend to experiment with HPF and LPF to get rid of unwanted resonances.
Convolution. A sum of random variables can be characterized exactly by a convolution formula. Let Y1, . . . , Yn be independent random variables and let fi(yi) denote the density of Yi for i=1 i = 1, . . . , n. Then for S = Σn Xx, the density of S can be written as the convolution: fS(S) = ∫Y2
Convolution. Center element of the kernel is placed over the source pixel. The source pixel is then replaced with a weighted sum of itself and nearby pixels.
Convolution. Center element of the kernel is placed over the source pixel. The source pixel is then replaced with a weighted sum of itself and nearby pixels. Source Pixel Convolution kernel (a.k.a. filter) New pixel value (destination pixel) 1 1 ∗ 0 + 1 ∗ 0 + 1 ∗ 0 + 1 ∗ 1 + 1 ∗ 1 + 1 ∗ 0 + 1 ∗ 2 + 1 ∗ 1 + 1 ∗ 0 = 0.6 ≈ 1 Top Middle
