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- deconvolution @glossary
- contexts ===== The most prominent application of deconvolution techniques is imaging. Usually one tries to remove blurring by deconvolution (or deconvolution-like) techniques. What holds for time domain data, also holds for imaging: Deconvolution has a disturbingly high potential for producing a
- reconvolution @glossary
- due to instrumental resolution. In contrast to [[deconvolution]], data processing using reconvolution techniques
- some_origins_of_multiexponetial_decays_for_single_dyes
- eir optimum may induce a "non perfect" [[glossary:deconvolution]] fit. But it is worth noting that even at magic
- how_to_measure_the_instrument_response_function_irf @howto
- lution]] method. The reason is simple: [[glossary:Deconvolution]] has many disadvantages: It is rather slow, it i