Search results
Results from the WOW.Com Content Network
The use of Richardson–Lucy deconvolution to recover a signal blurred by an impulse response function. The Richardson–Lucy algorithm, also known as Lucy–Richardson deconvolution, is an iterative procedure for recovering an underlying image that has been blurred by a known point spread function.
Engineers run simulations with this system-level model to verify performance against requirements and to optimize tunable parameters. System-level simulation is used to test controllers connected to the simulated system instead of the real one. If the controller is a hardware controller like an ECU, the method is called hardware-in-the-loop. If ...
Convolution and related operations are found in many applications in science, engineering and mathematics. Convolutional neural networks apply multiple cascaded convolution kernels with applications in machine vision and artificial intelligence. [36] [37] Though these are actually cross-correlations rather than convolutions in most cases. [38]
A convolutional neural network (CNN) is a regularized type of feed-forward neural network that learns features by itself via filter (or kernel) optimization. This type of deep learning network has been applied to process and make predictions from many different types of data including text, images and audio. [1]
The RTC Toolbox is an academic Java/MATLAB implementation of the Real-Time calculus framework, a theory quasi equivalent to network calculus. [4] [11] The CyNC [12] tool is an academic MATLAB/Symulink toolbox, based on top of the RTC Toolbox. The tool was developed in 2004-2008 and it is currently used for teaching at Aalborg university.
Dynamic simulation (or dynamic system simulation) is the use of a computer program to model the time-varying behavior of a dynamical system. The systems are typically described by ordinary differential equations or partial differential equations. A simulation run solves the state-equation system to find the behavior of the state variables over ...
The Volterra series is a model for non-linear behavior similar to the Taylor series.It differs from the Taylor series in its ability to capture "memory" effects. The Taylor series can be used for approximating the response of a nonlinear system to a given input if the output of the system depends strictly on the input at that particular time.
In mathematics, the convolution theorem states that under suitable conditions the Fourier transform of a convolution of two functions (or signals) is the product of their Fourier transforms. More generally, convolution in one domain (e.g., time domain) equals point-wise multiplication in the other domain (e.g., frequency domain).