1983/11/01 by Peter Gans, J. Bernard Gill · 2 citations
Chemistry · Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · #Spectroscopy and Chemometric Analyses #Spectroscopy Techniques in Biomedical and Chemical Research #Blind Source Separation Techniques #Convolution (computer science) #Smoothing #Distortion (music) #Noise (video) #Function (biology) #Set (abstract data type) #Mathematics #Noise reduction #Reduction (mathematics) #Overlap–add method #Algorithm #Data set #Computer science #Mathematical analysis #Statistics #Fourier transform #Artificial intelligence #Fourier analysis #Geometry #Telecommunications
paper · doi:10.1366/0003702834634712
openalex publication_date 1983/11/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/06/26
General expressions have been derived for the effects of convolution on a set of experimental data, from which the noise reduction may be predicted quantitatively. From these, a new criterion is proposed for the choice of convolution function in terms of the degree, number of convolution points, and number of passes of the convolution function through the data. This criterion gives maximal noise reduction with minimal signal distortion, and is particularly applicable in resolution enhancement applications. The new criteria have been tested with experimental data.