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The adjoint state method is a numerical method for efficiently computing the gradient of a function or operator in a numerical optimization problem. [1] It has applications in geophysics, seismic imaging, photonics and more recently in neural networks. [2] The adjoint state space is chosen to simplify the physical interpretation of equation ...
The proximal operator can be seen as a generalization of the projection operator. Indeed, in the specific case where f {\displaystyle f} is the 0- ∞ {\displaystyle \infty } characteristic function ι C {\displaystyle \iota _{C}} of a nonempty, closed, convex set C {\displaystyle C} we have that
Infix expressions are the form of mathematical notation most people are used to, for instance "3 + 4" or "3 + 4 × (2 − 1)". For the conversion there are two text variables , the input and the output. There is also a stack that holds operators not yet added to the output queue. To convert, the program reads each symbol in order and does ...
The syntax is matrix-based and provides various functions for matrix operations. It supports various data structures and allows object-oriented programming. [26] Its syntax is very similar to MATLAB, and careful programming of a script will allow it to run on both Octave and MATLAB. [27]
The artificial landscapes presented herein for single-objective optimization problems are taken from Bäck, [1] Haupt et al. [2] and from Rody Oldenhuis software. [3] Given the number of problems (55 in total), just a few are presented here. The test functions used to evaluate the algorithms for MOP were taken from Deb, [4] Binh et al. [5] and ...
Proximal gradient methods are applicable in a wide variety of scenarios for solving convex optimization problems of the form + (),where is convex and differentiable with Lipschitz continuous gradient, is a convex, lower semicontinuous function which is possibly nondifferentiable, and is some set, typically a Hilbert space.
Modern implementations for Boolean operations on polygons tend to use plane sweep algorithms (or Sweep line algorithms). A list of papers using plane sweep algorithms for Boolean operations on polygons can be found in References below. Boolean operations on convex polygons and monotone polygons of the same direction may be performed in linear ...
The most common source inputs for high-level synthesis are based on standard languages such as ANSI C/C++, SystemC and MATLAB. High-level synthesis typically also includes a bit-accurate executable specification as input, since to derive an efficient hardware implementation, additional information is needed on what is an acceptable Mean-Square ...