China 
Africa 
Explore chapters and articles related to this topic
Distance-Shape-Texture Signature Trio for Facial Expression Recognition
Published in Sourav De, Paramartha Dutta, Computational Intelligence for Human Action Recognition, 2020
Asit Barman, Sankhayan Choudhury, Paramartha Dutta
Each triangle hold the following basic properties: The sum of the angles in a triangle is 180 degrees. This is called the angle-sum property.The sum of the lengths of any two sides of a triangle is greater than the length of the third side. Similarly, the difference between the lengths of any two sides of a triangle is less than the length of the third side.The side opposite to the largest angle is the longest side of the triangle and the side opposite to the smallest angle is the shortest side of the triangle.
Maths and science for engineering
Published in Mike Tooley, Engineering GCSE, 2012
Now the sum of the angles in a triangle is 180°. Hence: θ+45∘+60∘=180∘
A few basic rules
Published in James Kidd, Ian Bell, Maths for the Building Trades, 2014
The answer obtained when numbers are added together is called the sum. Numbers can be added together in any order; for example, adding together the numbers 2 + 4 + 6 will give the same answer (12) as 4 + 6 + 2 or 6 + 4 + 2.
Human arm motion prediction in human-robot interaction based on a modified minimum jerk model
Published in Advanced Robotics, 2021
Jing Zhao, Shiqiu Gong, Biyun Xie, Yaxing Duan, Ziqiang Zhang
The curve of the modification item needs to have the above three characteristics. After observing the curves of a variety of mathematical functions, four functions that satisfy these requirements are found. They are the Fourier series, the polynomial function, the Gaussian function, and the sine sum function. Considering the suitable model error and model complexity, we determined the equations for these alternatives, which are second-order Fourier series (Fourier2), quintic polynomial (Poly5), second-order Gaussian (Gauss2), and the second-order sine sum function (Sin2). We use these four equations to model the errors and compare their performance to find the optimal equation. Three evaluation indicators judge the performance of these functions: the Goodness of Fit (R2), the Mean Absolute Error (MAE), and the Root Mean Squared Error (RMSE). All motion samples in Section 2.2.1 are involved.
Stability and L 1 × ℓ1-to-L 1 × ℓ1 performance analysis of uncertain impulsive linear positive systems with applications to the interval observation of impulsive and switched systems with constant delays
Published in International Journal of Control, 2020
Several methods can be used to check the conditions stated in Theorems 3.1–3.4. The piecewise linear discretization approach (Allerhand & Shaked, 2011; Briat, 2017a; Xiang, 2015) assumes that the decision variables are piecewise linear functions of their arguments and leads to a finite-dimensional linear programme that can be checked using standard linear programming algorithms. Another possible approach is based on Handelman's Theorem (Handelman, 1988) and also leads to a finite-dimensional programme (Briat, 2013a, 2017a). We opt here for an approach based on Putinar's Positivstellensatz (Putinar, 1993) and semidefinite programming (Parrilo, 2000).1 Before stating the main result of the section, we need to define first some terminology. A multivariate polynomial is said to be a sum-of-squares (SOS) polynomial if it can be written as for some polynomials . A polynomial matrix is said to componentwise sum-of-squares (CSOS) if each of its entries is an SOS polynomial. Checking whether a polynomial is SOS can be exactly cast as a semidefinite programme (Chesi, 2010; Parrilo, 2000) that can be easily solved using semidefinite programming solvers such as SeDuMi (Sturm, 2001). The package SOSTOOLS (Papachristodoulou et al., 2013) can be used to formulate and solve SOS programmes in a convenient way.
A Neumann series of Bessel functions representation for solutions of perturbed Bessel equations
Published in Applicable Analysis, 2018
Vladislav V. Kravchenko, Sergii M. Torba, Raúl Castillo-Pérez
Consider the functions and , . The function is a polynomial of degree 2N and is a partial sum of the Fourier–Legendre series of g, i.e. coincides with the polynomial of the best approximation of the function g by polynomials of degree 2N. Hence by Theorem 6.3 from [20, Chapter 7] for any , there exists a universal constant such that , . We take . Then using the estimates (4.4) and (4.7), we obtain that