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An example of a closed-loop block diagram, from which a transfer function may be computed, is shown below: The summing node and the G(s) and H(s) blocks can all be combined into one block, which would have the following transfer function: () = + ()
Block-matching and 3D filtering (BM3D) is a 3-D block-matching algorithm used primarily for noise reduction in images. [1] It is one of the expansions of the non-local means methodology. [ 2 ] There are two cascades in BM3D: a hard-thresholding and a Wiener filter stage, both involving the following parts: grouping, collaborative filtering ...
McClellan transformations [8] can be used to transform a 1D filter design into a 2D filter design by using a transformation function. This theory allows the design of 2D adaptive filters [9] out of existing 1D prototype filters. Compared to the direct approach, this system has the advantages of a lower computational complexity and a faster ...
Simulink is a MATLAB-based graphical programming environment for modeling, simulating and analyzing multidomain dynamical systems. Its primary interface is a graphical block diagramming tool and a customizable set of block libraries. It offers tight integration with the rest of the MATLAB environment and can either drive MATLAB or be scripted ...
The recording of a heart beat (an ECG), may be corrupted by noise from the AC mains.The exact frequency of the power and its harmonics may vary from moment to moment.. One way to remove the noise is to filter the signal with a notch filter at the mains frequency and its vicinity, but this could excessively degrade the quality of the ECG since the heart beat would also likely have frequency ...
A block diagram is a diagram of a system in which the principal parts or functions are represented by blocks connected by lines that show the relationships of the blocks. [1] They are heavily used in engineering in hardware design , electronic design , software design , and process flow diagrams .
The Smith predictor (invented by O. J. M. Smith in 1957) is a type of predictive controller designed to control systems with a significant feedback time delay. The idea can be illustrated as follows.
The causal finite impulse response (FIR) Wiener filter, instead of using some given data matrix X and output vector Y, finds optimal tap weights by using the statistics of the input and output signals. It populates the input matrix X with estimates of the auto-correlation of the input signal (T) and populates the output vector Y with estimates ...