136 skills found · Page 4 of 5
Tinysimpler / Neural Network Nonlinear Function Fitting Based On Particle Swarm Optimization AlgorithmsPSO , Simulated Annealing PSO , Chaotic SAPSO, Neural network, Nonlinear Function
loopspace / JsHobbyA javascript implementation of the quick version of Hobby's algorithm for curve fitting
ekirving / QpbruteHeuristic search algorithm for fitting qpGraph models
kadlecpt / VFTool 0.1Vector Fitting Tool in MATLAB
adityadj98 / Computational Methods In Pricing And Model Calibration Columbia UniversityThis course focuses on computational methods in option and interest rate, product’s pricing and model calibration. The first module will introduce different types of options in the market, followed by an in-depth discussion into numerical techniques helpful in pricing them, e.g. Fourier Transform (FT) and Fast Fourier Transform (FFT) methods. We will explain models like Black-Merton-Scholes (BMS), Heston, Variance Gamma (VG), which are central to understanding stock price evolution, through case studies and Python codes. The second module introduces concepts like bid-ask prices, implied volatility, and option surfaces, followed by a demonstration of model calibration for fitting market option prices using optimization routines like brute-force search, Nelder-Mead algorithm, and BFGS algorithm. The third module introduces interest rates and the financial products built around these instruments. We will bring in fundamental concepts like forward rates, spot rates, swap rates, and the term structure of interest rates, extending it further for creating, calibrating, and analyzing LIBOR and swap curves. We will also demonstrate the pricing of bonds, swaps, and other interest rate products through Python codes. The final module focuses on real-world model calibration techniques used by practitioners to estimate interest rate processes and derive prices of different financial products. We will illustrate several regression techniques used for interest rate model calibration and end the module by covering the Vasicek and CIR model for pricing fixed income instruments.
tylergrreid / L5 SBAS MOPS Ephemeris Fitting AlgorithmThis matlab code fits the L5 SBAS MOPS ephemeris message parameters to precision orbit data. It also performs fit error analysis and evaluates the message performance. Specificially, this looks at the corner cases that can cause problems with the fitting algorithm convergence. This implements the algorithms outlined in Appendix B of my PhD thesis undertaken in the GPS Research Lab in the Department of Aeronautics and Astronautics at Stanford University, entitled, "Orbital Diversity for Global Navigation Satellite Systems"
yaochx / CuLMFitting with Levenberg-Marquardt algorithm in CUDA
codeXing8 / BevlshaperAlgorithm for bird's-eye-view L-shape fitting in 3D LIDAR point clouds from traffic scenarios
Esri / Dito.tsJavascript oriented bounding box construction using the DiTO algorithm from "Fast Computation of Tight-Fitting Oriented Bounding Boxes" of the book "Game Engine Gems 2"
neycyanshi / Plane FittingRANSAC algorithm with a line/plane fitting example of raw depth map.
nyakasko / LO RANSAC 3DPlaneFittingImplementation of the Locally Optimized Random SAmple Consensus (LO-RANSAC) 3D plane fitting algorithm
mrpositron / Sphere FittingThis project is a demonstration of a simple sphere fitting algorithm using a neural network to guide the RANSAC algorithm.
ntotorica / SMP Passivity EnforcementAuthor: Nathan Totorica Date: 5/14/2021 # Singularity Matrix Pertubation (SMP) This code was written for a class project in the course entitled ECE 504: "ST: Passive Electromagnetic Systems" taught in Spring 2021 by Dr. Ata Zadehgol at the University of Idaho in Moscow. This code was developed, in part, based on the code developed by Jennifer Houle in ECE 504 "ST: Modern Circuit Synthesis Algorithms" taught in Spring 2020 by Dr. Ata Zadehgol. Jennifer's code is available online at https://github.com/JenniferEHoule/Circuit_Synthesis. ## Overview Singular Matrix Perturbation (SMP) as introduced in [11], is a passivity enforcement algorithm for use on fitted models. This robust method is fast, computationally inexpensive, and accurate in enforcing passivity. This implementation using Python can easily be used with Vector Fitting algorithm implemented in [12]. Example cases to demonstrate passivity enforcmment were taken from [7][15], as well as custom examples designed in simulation software based off of multiport circuit synthesis as described in [6]. ## I/O and Flow Description - Instructions for input and output and flow description can be found in flow_diagram.pdf. ## Files - SMP.py: Singularity matrix perturbation implementation of [11] - s_compare.py: Compare ADS simulated S matrices. Calculate RMS error and plot - eig_plot.py: Plotting functions. Eigenvalue plots based off of plot.py in [12] - smp_ex.py: Example of how to pull .sp file in, parse parameters, send to vector fitting, enforce passivity, and generate new passive circuit. Imported from [12] - Ex2_y.py - vectfit3.py - intercheig.py - rot.py - pass_check.py - fitcalc.py - FRPY.py - intercheig.py - violextrema.py - plots.py - quadprog.py - pr2ss.py - utils.py ## Licensing GPL-3.0 License In addition to licensing: Embedding any of (or parts from) the routines of the Matrix Fitting Toolbox in a commercial software, or a software requiring licensing, is strictly prohibited. This applies to all routines, see Section 2.1. If the code is used in a scientific work, then reference should me made as follows: VFdriver.m and/or vectfit3.m: References [1],[2],[3] RPdriver.m and/or FRPY.m applied to Y-parameters: [8],[9] ## References [1] B. Gustavsen and A. Semlyen, "Rational approximation of frequency domain responses by Vector Fitting", IEEE Trans. Power Delivery, vol. 14, no. 3, pp. 1052-1061, July 1999. [2] B. Gustavsen, "Improving the pole relocating properties of vector fitting", IEEE Trans. Power Delivery, vol. 21, no. 3, pp. 1587-1592, July 2006. [3] D. Deschrijver, M. Mrozowski, T. Dhaene, and D. De Zutter, "Macromodeling of Multiport Systems Using a Fast Implementation of the Vector Fitting Method", IEEE Microwave and Wireless Components Letters, vol. 18, no. 6, pp. 383-385, June 2008. [4] B. Gustavsen, VFIT3, The Vector Fitting Website. March 20, 2013. Accessed on: Jan. 21, 2020. [Online]. Available: https://www.sintef.no/projectweb/vectfit/downloads/vfit3/. [5] A. Zadehgol, "A semi-analytic and cellular approach to rational system characterization through equivalent circuits", Wiley IJNM, 2015. [Online]. https://doi.org/10.1002/jnm.2119 [6] V. Avula and A. Zadehgol, "A Novel Method for Equivalent Circuit Synthesis from Frequency Response of Multi-port Networks", EMC EUR, pp. 79-84, 2016. [Online]. Available: ://WOS:000392194100012. [7] B. Gustavsen, Matrix Fitting Toolbox, The Vector Fitting Website. March 20, 2013. Accessed on: Feb. 25, 2020. [Online]. Available: https://www.sintef.no/projectweb/vectorfitting/downloads/matrix-fitting-toolbox/. [8] B. Gustavsen, "Fast passivity enforcement for S-parameter models by perturbation of residue matrix eigenvalues", IEEE Trans. Advanced Packaging, vol. 33, no. 1, pp. 257-265, Feb. 2010. [9] B. Gustavsen, "Fast Passivity Enforcement for Pole-Residue Models by Perturbation of Residue Matrix Eigenvalues", IEEE Trans. Power Delivery, vol. 23, no. 4, pp. 2278-2285, Oct. 2008. [10] A. Semlyen, B. Gustavsen, "A Half-Size Singularity Test Matrix for Fast and Reliable Passivity Assessment of Rational Models," IEEE Trans. Power Delivery, vol. 24, no. 1, pp. 345-351, Jan. 2009. [11] E. Medina, A. Ramirez, J. Morales and K. Sheshyekani, "Passivity Enforcement of FDNEs via Perturbation of Singularity Test Matrix," in IEEE Transactions on Power Delivery, vol. 35, no. 4, pp. 1648-1655, Aug. 2020, doi: 10.1109/TPWRD.2019.2949216. [12] Houle, Jennifer, GitHub. May 10, 2020. Accessed on: February 3, 2021. [Online]. Available: https://github.com/jenniferEhoule/circuit_synthesis
edervishaj / Genetic Linear RegressionApproximation of linear regression fitting through genetic algorithm.
gregkepler / CinderPathFitterPath Fitting Algorithm for the Cinder C++ Framework
avaneev / AreafitterFit Multiple Smaller Rectangles Into Larger Rectangles or Images - Iterative Permutational Optimization Method
ChrisZonghaoLi / Motion Tracking Using MagnetometerMotion Tracking Using Magnetometer Based On Ellipsoid Fitting Algorithm
NNU-GISA / BevlshaperAlgorithm for bird's-eye-view L-shape fitting in 3D LIDAR point clouds from traffic scenarios
pavolgaj / OCFitPython package for fitting of O-C diagrams.
zygmuntszpak / Guaranteed Ellipse Fitting With Sampson DistanceA MATLAB implementation of a new ellipse fitting algorithm that uses an approximate maximum likelihood cost function to fit an ellipse to data, and simultaneously guarantees that an ellipse will be produced.
