T(n)=4T(n/2)+f(n), in which f(n)=O(n)f(n)=O(n) the time complexity of polynomial addition. Using the Master Theorem with a=4,b=2,logba=log24=2>1a=4,b=2,logba=log24=2>1, we have T(n)=O(nlogba)=O(n2)T(n)=O(nlogba)=O(n2). So, let's ...
evaluationalgorithm.ItissuitableforVLSIimplementationand thecomputationalcostisreducedtoabout66%ofthepreviously reportedmethod. I.CBIC-POLYNOMIALEVALUATIONALGORITHM Cubic-polynomialevaluationisacommonlyusedmethod inmeasurementandinstrumentation[1],[2].Amongthe
Using these unique prefixes, we build two binary tries, one for field F1 (F1 trie) and the other for field F2 (F2 trie). Each node containing a valid prefix is associated with a bit vector of size 8. The size of the bit vector, as noted earlier, is the same as the number of ...
This research attempts to reinforce the cultivating expression of radial basis function neural network (RBFnet) through computational intelligence (CI) and
The bigmatrix package enables multiplication, addition and subtraction of matrices with entries that are bignumber instances. It also implements operations between bignumber instances and int64 instances, so PSLQ can run a bit faster before it switches over to using bignumber for almost all operations...
,ϕD)T. There exists a broad range of basic functions, such as polynomial, gaussian, radial, and sigmoidal basic functions, which should be chosen with respect to the application [66,68]. For training the model, there exists a range of approaches: Ordinary Least Square, Regularized Least ...
To find G-optimal designs for more complicated models, Sect. 5 introduces a nature-inspired meta-heuristic algorithm called competitive swarm optimizer (CSO) to find G-optimal designs for more complicated hierarchical linear models, such as, when the mean function is a fractional polynomial and ...
There is no doubt that mAHA has an advantage over the algorithms which are compared for multi-modal functions F2, F3, and F4 in terms of performance. Nevertheless, regarding the F4 function, the most accurate values can be obtained using mAHA, AHA, RUN, and SMA. In addition, the proposed...
SVM work developing classifiers or diagnosis models by using kernel functions. A polynomial function of second degree fits better the TEP data used to construct the models. SVM use the PCA scores and the corresponding labels (assignation of the scores to the corresponding process scenario, either ...
To find to minimum value for all points is finding the sliding minimum over an array. All minimal points can be found with a double-ended queue in O(|Q|). The full Algorithm RRH is described in Algorithm 2. Creating all Htτ has a time complexity of O(n· |Q|). The overall time...