In order to increase the accuracy of timing estimation in frequency selective fading (FSF) channels and reduce the computational complexity, in this paper an adaptive symbol synchronization of OFDM blind channel estimation is proposed. First, by the ML algorithm used in flat fading channels, we giv...
In the proposed algorithm, the authors use two steps to maximise an ML metric to obtain first the frequency offset and then timing. A fast Fourier transform algorithm is used to estimate the frequency offset. Using these two estimates, the channel is identified. A simple iterative algorithm is...
This approach used the ratio of the between- to within-groups sum of squares, i.e., the ratio BWR, as an initial weight within the L1-norm of the elastic net model. There were few examples of embedding-based unsupervised and semisupervised ML algorithms in the literature. For example, ...
Machine learning algorithms are widely used in ATS systems like Alguliyev, Aliguliyev, Isazade, Abdi, and Idris (2019), Shetty and Kallimani (2017), Yousefi-Azar and Hamey (2017). Machine learning algorithms are categorized as: supervised, unsupervised, or semi-supervised. Supervised Learning ...
Finally, it is showed that the extracted features can also be used in feature based probabilistic SLAM methods such as Kalman Filters, Information Filters, and Particle Filters after applying merging procedure. Since the plane segments are already registered, the data association problem can be ...
A large number of features can bog down some learning algorithms, making training time unfeasibly long.Support vector machinesare well suited to scenarios with a high number of features. For this reason, they have been used in many applications from information retrieval to text and image classifi...
In the paper, a novel inversion approach is used for the solution of the problem of factor analysis. The float-encoded genetic algorithm as a global optimi... NP Szabó,M Dobróka - 《Mathematical Geosciences》 被引量: 1发表: 2018年 A Comparative Study of Simulated Annealing and Genetic Al...
Batch normalization is a technique used to standardize inputs in ANNs, enabling the effective training of the network. It boosts accuracy by allowing all layers to be trained, but this may come at the cost of reduced efficiency. Progressive batch normalization has been developed to achieve signifi...
In supervised learning, each data point is labeled or associated with a category or value of interest. An example of a categorical label is assigning an image as either a ‘cat’ or a ‘dog’. An example of a value label is the sale price associated with a used car. The goal of supe...
object 2 into bin 2. Object 3 fits into the first bin and is placed there. Object 4 does not fit into either of the two bins used so far and a new bin is used. The solution produced utilizes 3 bins and has objects 1 and 3in bin I, object 2in bin 2, and object 4in bin 3...