With the large number of antennas and subcarriers overhead due to pilot transmission for channel estimation can be prohibitive in wideband massive multiple-input multiple-output (MIMO) systems. This degrade overall spectral efficiency significantly, as a result, curtail potential benefits MIMO. In this paper, we propose neural network (NN)-based joint design downlink scheme frequency division d...

A method that allows us to give a different treatment to any neuron inside feedforward neural networks is presented. The algorithm has been implemented with two very different learning methods: a standard Back-propagation (BP) procedure and an evolutionary algorithm. First, we have demonstrated that the EA training method converges faster and gives more accurate results than BP. Then we have ma...

Systems for predictive text entry on ambiguous keyboards typically rely on dictionaries with word frequencies which are used to suggest the most likely words matching user input. This approach is insufficient for agglutinative languages, where morphological phenomena increase the rate of out-of-vocabulary words. We propose a method for text entry, which circumvents the problem of out-of-vocabul...

We describe an experimental study of pruning methods for decision tree classi ers when the goal is minimizing loss rather than error. In addition to two common methods for error minimization, CART's cost-complexity pruning and C4.5's error-based pruning, we study the extension of cost-complexity pruning to loss and one pruning variant based on the Laplace correction. We perform an empirical com...

Fine-tuning transformer models after unsupervised pre-training reaches a very high performance on many different natural language processing tasks. Unfortunately, transformers suffer from long inference times which greatly increases costs in production. One possible solution is to use knowledge distillation, solves this problem by transferring information large teacher smaller student models. K...

Most machine learning solutions to noun phrase coreference resolution recast the problem as a classification task. We examine three potential problems with this reformulation, namely, skewed class distributions, the inclusion of “hard” training instances, and the loss of transitivity inherent in the original coreference relation. We show how these problems can be handled via intelligent sample ...

Systems for predictive text entry on ambiguous keyboards typically rely on dictionaries with word frequencies which are used to suggest the most likely words matching user input. This approach is insufficient for agglutinative languages, where morphological phenomena increase the rate of out-of-vocabulary words. We propose a method for text entry, which circumvents the problem of out-of-vocabul...

the present article investigates the application of high order tsk (takagi sugeno kang) fuzzy systems in modeling photo voltaic (pv) cell characteristics. a method has been introduced for training second order tsk fuzzy systems using anfis (artificial neural fuzzy inference system) training method. it is clear that higher order tsk fuzzy systems are more precise approximators while they cover n...