The super-exponential algorithm is a block-based technique for blind channel equalization and system identi cation. Due to its fast convergence rate, and no a priori parameterization other than the block length, it is a useful tool for linear equalization of moderately distortive channels. This paper presents a recursive implementation of the super-exponential algorithm for fractionally-sampled...

Spectrum monitoring is one of the significant tasks required during spectrum sharing process in cognitive radio networks (CRNs). Although widely used to monitor usage allocated resources, this work focuses on detecting a primary user (PU) presence secondary (SU) signals. For signal classification, existing methods, including cooperative, noncooperative, and neural network-based models, are freq...

This paper deals with an improved demodulation technique for LoRa signal. The principle consists of detecting the possible errors demodulation, by comparing highest peak periodogram dechirped received signal weighted a coefficient β other peaks periodogram. If error is detected, second stage processed at oversampling rate (OSR) higher than first stage. Otherwise, result kept. A thorough perform...

This study presents the development of a novel integrated data fusion and assimilation technique to classify learning experiences patterns among deaf students using Fleming’s model together with Thai Sign Language. Data were collected from hearing disabilities (Grades 7–9) studying at special schools in Khon Kaen Udon Thani, Thailand. research used six classification algorithms being resynthesi...

This paper presents a 71MS/s oversampling D/A converter for DMT-ADSL applications and focuses on the design and performance analysis of the sigma-delta modulator. Design trade-off among the interpolator, current-mode semi-digital FIR filter and analog continuous-time filter has also been discussed. By optimizing the NTF zeros of the 5-th order modulator with an oversampling ratio of 32, the D/A...

Developmening systems applying machine learning and data mining techniques is one of the approaches to combating network intrusion.Many IDS Intrusion Detection Systems)suffer from a high rate of false alarms and missed intrusions.Tha challenge is to be able to improve the intrusion detection rate at a reduced false positive rate. To counter imbalance in data, a combination of oversampling (synt...

This work is devoted to an adaptive multiscale finite element method (MsFEM) for solving elliptic problems with rapidly oscillating coefficients. Starting from a general version of the MsFEM with oversampling, we derive an a posteriori estimate for the H-error between the exact solution of the problem and a corresponding MsFEM approximation. Our estimate holds without any assumptions on scale s...

This paper is mainly tutorial in nature and discusses architectures for oversampling converters with a particular emphasis on those which are well suited for high frequency input signal bandwidths. The first part of the paper looks at various architectures for discrete-time modulators and looks at their performance when attempting high speed operation. The second part of this paper presents som...

In this paper we investigate the achievable rate of LOS MIMO systems that use 1-bit quantization and spatial oversampling at the receiver. We propose that by using additional antennas at the receiver, the loss incurred due to the strong limitation of the quantization can be decreased. Mutual information results show that considerable rate gains can be achieved depending on the number and arrang...

A class of non-canonical duals for the multiwindow Gabor scheme, incorporating both rational and integer oversampling of the Gaborian combined time-frequency space, is considered. Using properties of Gabor frame matrices, block Discrete Fourier transforms, and results from number theory, we establish existence conditions for the noncanonical duals for both integer and rational oversampling rate...