high frequency classifier

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  Forecasting trends of high-frequency KOSPI200 index data using …

  20121015 · Trends of high-frequency KOSPI200 index are predicted with learning classifiers. High-frequency spot trends are better predictable with spot & futures. Virtual trading using the trained classifiers shows noticeable better profits.

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  Naive Bayes Classifier : Definition, Applications …

  2016121 · Abstract In this paper, a Hierarchical Polynomial (HP) classifier is proposed to automatically classify M-PSK and M-QAM signals in Additive White Gaussian Noise (AWGN) and slow flat fading environments. The system uses higher order cumulants (HOCs) of the received signal to distinguish between the different modulation types. The …

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  Robust dual-tone multi-frequency tone detection using k …

  202141 · Robust dual-tone multi-frequency tone detection using k-nearest neighbour classifier for a noisy environment - Author: Arunit Maity, P. Prakasam, Sarthak Bhargava

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  Automated sleep stage identification system based on time–frequency ...

  2012101 · Highlights A new method for automated sleep scoring is proposed. A new technique based on time–frequency analysis of EEG signal is proposed. Random forest classifier has successfully classified sleep stages.

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  Energies | Free Full-Text | Revisiting Adaptive Frequency

  202118 · Thanks to the frequency hopping nature of Bluetooth, sniffing Bluetooth traffic with low-cost devices has been considered as a challenging problem. To this end, BlueEar, a state-of-the-art low-cost sniffing system with two Bluetooth radios proposes a set of novel machine learning-based subchannel classification techniques for adaptive …

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  Diversity and diachronic change in the classifier system of …

  2014111 · This article examines the origins and use of the three principal high frequency classifiers used in Xianghua, an unclassified language spoken in Xiangxi, Northwestern Hunan.

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  Frequency-Selective Adversarial Attack Against Deep …

  2024110 · Although Deep learning (DL) provides state-of-art results for most spectrum sensing tasks, it is vulnerable to adversarial examples. Based on this phenomenon, we consider a noncooperative communication scenario where an intruder tries to recognize the modulation type of the intercepted signal. Specifically, this paper aims to minimize the …

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  Machine learning based KNN classifier: towards robust, …

  Owing to the continuous and rapid evolution of telecommunication equipment, the demand for a more efficient and noise-robust detection of Dual-tone multi-frequency (DTMF) signals is conspicuous. In this research article, a novel machine learning based approach to detect DTMF tones perturbed by noise, frequency and time variations by employing the K …

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  Vibration-based monitoring of agro-industrial machinery …

  202421 · Semantic Scholar extracted view of "Vibration-based monitoring of agro-industrial machinery using a k-Nearest Neighbors (kNN) classifier with a Harmony Search (HS) frequency selector algorithm" by F. Gomez-Gil et al.

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