if for every weakly convergent subsequence \(v^{(n)}\rightharpoonup \hat{v}\) we have $$\begin{aligned} \liminf _{v^{(n)}\rightharpoonup \hat{v}} {\mathcal j}(v^{(n)}) \ge {\mathcal j}(\hat{v}). \end{aligned}$$ for a convex functional \({\mathcal j}: {\math...
the space\(\mathrm {BV}\)of functions with bounded variation has to be introduced by a relaxation approach [39] that makes use of the notion of upper gradients. An alternative approach to\(\mathrm
I am trying to solve thisproblemon spoj. The problem gives an input of n integers and then asks q queries which are of the form l r k and the program has to output number of elements greater than k in the subsequence al, al+1, ..., ar. I am using persistent segment trees to p...
Longest Palindromic Subsequence Preorder to Postorder of BST Maximum difference of zeros and ones in binary string Sum of all substrings of a number NAJPF - Pattern Find Arrays Coding Problems Sort an array of 0's, 1's and 2's in linear time complexity Check for Valid Sudoku Palindromic ...
Problem : You are given an array of N integers. You have to print the total number of strictly decreasing subsequences of the array ? Note : You cannot consider a single element to be in any strictly decreasing subsequence.(At least two elements are needed to form a strictly decreasing subs...
has a subsequence weakly converging to an invariant measure of the markov chain with transition probability \(q^i(\cdot \mid \cdot ,f^i,\overline{\tau })\) . let us call it \(\mu _{f^i,\overline{\tau }}\) . it can be easily showed that \(\delta _w^m(s^i)\) is tight...
Since a subsequence of \{\Sigma _k\cap B_{{{\mathrm{{\mathbb {R}}}^3}(0,\lambda _nr_n)\}_{k\ge n} converges to \widetilde{\Sigma }\cap B_{{{\mathrm{{\mathbb {R}}}^3}(0,\lambda _nr_n), then for k sufficiently large, we have that \begin...
Nevertheless, the orders of Papp for the six analytes in rats perfused with MDQ-TS at high concentration level (5.0 mg·mL−1) appeared the following subsequence: duodenum ≈ jejunum > ileum (p < 0.05 for C1, C3, C4, and DC1). Table 1. Papp and Ka of C1, C2, C3, C4, DC1, ...
22. iterative subsequence dynamic time warping, 23. particle filtering, 24. Maximum a Posteriori (MAP) criteria, 25. Gaussian Process Classifiers, 26. rule-based classifiers, 27. decision trees, 28. Adaboost classifiers, 29. several supervised classifiers, 30. Self-Optimizing Mapping (SOM), 31...