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Lecture notes on the design of low-pass digital filters with wireless-communication applications
These lecture notes are part of a short course that is intended to help recent engineering graduates design low-pass digital filters for this purpose, who have had some exposure to the topic during their studies, and who are now interested in the sending and receiving signals over the electromagnetic spectrum, in wireless communication (i. e. radio) and remote sensing (e. g. radar) applications, for instance.
Noise will be noise: Or phase optimized recursive filters for interference suppression, signal differentiation and state estimation (extended version)
Such filters are readily designed via flatness constraints on the derivatives of the complex frequency response at dc, pi and at the centre frequencies of narrowband interferers, i. e. using maximally-flat (MaxFlat) designs.
Digital filters with vanishing moments for shape analysis
Expressions for the coefficients of a low-order IIR blur filter with repeated poles are provided, as a function of scale; discrete Butterworth (IIR), and colored Savitzky-Golay (FIR), blurs are also examined.
On the Realization and Analysis of Circular Harmonic Transforms for Feature Detection
Circular-harmonic spectra are a compact representation of local image features in two dimensions.
Multidimensional Digital Smoothing Filters for Target Detection
Recursive, causal and non-causal, multidimensional digital filters, with infinite impulse responses and maximally flat magnitude and delay responses in the low-frequency region, are designed to negate correlated clutter and interference in the background and to accumulate power due to dim targets in the foreground of a surveillance sensor.
Parallel software implementation of recursive multidimensional digital filters for point-target detection in cluttered infrared scenes
A technique for the enhancement of point targets in clutter is described.
Multidimensional Digital Filters for Point-Target Detection in Cluttered Infrared Scenes
Velocity estimates are then used to tune in a background-whitening PEF that is matched to the motion and texture of the local background.
