Phong, and so on). Therefore, each function's coefficients can be computed once (in a preprocess step) and be reused by all convolutions. This optimization reduces the runtime complexity of the example convolution to just
Each sequence edge on its turn has a pointer to a register conflict (if there is one) and the matrix entry representing the path that gave rise to the edge. The complexity of the infeasibility analysis is thus bounded by O(E· log E). We assume, however, that the longest paths have ...
This paper describes an algorithm which computes the characteristic polynomial of a matrix over a field within the same asymptotic complexity, up to constant factors, as the multiplication of two square matrices. Previously, this was only achieved by resorting to genericity assumptions or randomization...
foregoing all-vs-all sequence alignments in favor of a dynamic data structure implemented in GoldRush, a de novo long read genome assembly algorithm with linear time complexity. We tested GoldRush on Oxford Nanopore Technologies long sequencing read datasets with different base error profiles sourced ...
Intestinal tract physiology relies on the integrated contribution of multiple cell lineages, the relative abundance and cell networking of which fluctuate from embryonic development to adulthood. Further complexity is added because the intestinal tract is formed of distinct anatomical regions that develop at...
The complexity of the algorithm can be expressed as O(n2) [18]. In order to solve the problem of automated guided vehicle (AGV) access path planning in the smart garage and overcome the shortcomings of the traditional Dijkstra algorithm such as high time complexity, large search range, and ...
It not only overcomes the computational complexity, training inefficiency, and difficulty of the practical application of RNN but also avoids the problem of locally optimal solutions. ESN mimics the structure of recursively connected neuron circuits in the brain and consists of an input layer, an ...
[1,4]. An efficient integrator that preserves symmetry and anti-symmetry and uses them to reduce the computational complexity, is needed in these and other applications, such as using a step of the integrator as a computationally efficient retraction in optimization algorithms for (anti-)symmetric...
With the continual development of the global economy, the air transportation demand has significantly increased across various industries, leading to a surge in flight traffic and airspace complexity. To optimize flight scheduling and improve operational efficiency, the traffic prediction is extensively stu...
Time series classification (TSC) is a form of machine learning where the features of the input vector are real valued and ordered. This scenario adds a layer of complexity to the problem, as important characteristics of the data can be missed by traditional algorithms. Over recent years, a ne...