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[PDF] Top 20 Low-complexity methods for autoregressive signal modeling

Has 7457 "Low-complexity methods for autoregressive signal modeling" found on our website. Below are the top 20 most common "Low-complexity methods for autoregressive signal modeling".

Low-complexity methods for autoregressive signal modeling

Low-complexity methods for autoregressive signal modeling

... efficient methods for parameter estimation in 1st and 2nd order AR ...the low-complexity parameter estimation problem in the AR(1) case using a binarized process and a piecewise linear curve ... See full document

86

Signal processing methods for large-scale multi-antenna systems

Signal processing methods for large-scale multi-antenna systems

... strongly benefit from this technology, including MIMO heterogeneous networks with wireless backhauling (NI et al., 2019), terahertz communication systems (AKYILDIZ; JORNET, 2016) and mmWave unmanned aerial vehicle ... See full document

188

Analysis of Mouse Periodic Gene Expression Data Based on Singular Value Decomposition and Autoregressive Modeling

Analysis of Mouse Periodic Gene Expression Data Based on Singular Value Decomposition and Autoregressive Modeling

... series signal in PSM rhythmically ...five methods and the results shos that the Stable persistence (S) method has the best performance by identifying most of the benchmark probe sets sithin the top 300 ... See full document

4

Performance Evaluation of Low Complexity Massive MIMO Techniques for SC-FDE Schemes

Performance Evaluation of Low Complexity Massive MIMO Techniques for SC-FDE Schemes

... whose methods of sending and processing data is mostly handled by advanced computer ...the signal via the space propagation medium, it is necessary to convert them from its digital domain to the analogue ... See full document

112

Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry.

Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry.

... is modeling spectral signals by mixtures of component ...mixture modeling for protein MS spectra are highlighted in the referenced studies ...detection methods the information on shapes is ...of ... See full document

19

METHODS FOR QUALITY ENHANCEMENT OF USER VOICE SIGNAL IN VOICE AUTHENTICATION SYSTEMS

METHODS FOR QUALITY ENHANCEMENT OF USER VOICE SIGNAL IN VOICE AUTHENTICATION SYSTEMS

... the signal/noise ratio of the user voice signal in the authentication system is ...voice signal of authentication system user in computer systems and ...networks. Methods and means for input ... See full document

6

A Novel Positioning Technique with Low Complexity in Wireless LAN: Hardware implementation

A Novel Positioning Technique with Low Complexity in Wireless LAN: Hardware implementation

... LOS signal but a strong specular reflection off a smooth surface such as that of a large building will give rise to similar ...received signal will be strong and with moderate ...received signal is ... See full document

7

Behavioral modeling optimization and enhancement for high-speed analog mixed-signal I/O interfaces

Behavioral modeling optimization and enhancement for high-speed analog mixed-signal I/O interfaces

... The approaches [11]-[15] differ in the model formulation and identification process for capturing the behavior of the PU and PD devices. For example, the IBIS model assumes static local models for and , which are thus ... See full document

115

Saturation in autoregressive models

Saturation in autoregressive models

... In this paper we have established that the impulse saturation method can also be applied to stationary AR(1) models. Monte Carlo evidence has shown that nominal and real size are close for this type of model. There are ... See full document

14

Evaluating the use of ECG signal in low frequencies as a biometry

Evaluating the use of ECG signal in low frequencies as a biometry

... This section describes the methodology employed for perform- ing the proposed evaluations. First, the ECG signal is sampled in a specific frequency and then it is preprocessed. Then, ECG fiducial points are ... See full document

7

VHDL Modeling, Simulation and Prototyping of a Novel Arbitrary Signal Generation System

VHDL Modeling, Simulation and Prototyping of a Novel Arbitrary Signal Generation System

... Arbitrary signal generators play an important role in many ...present modeling, simulation and prototyping of a novel periodic arbitrary signal generation system using ...the signal generated ... See full document

8

Modeling and simulation of a solar cavity receiver for low latitudes

Modeling and simulation of a solar cavity receiver for low latitudes

... The low pressure of those salts in comparison to steam made possible to use much thinner walled tubes in the receiver, reducing thermal stresses, added to better heat transfer characteristics, increasing the ... See full document

138

An Efficient Parallel Algorithm for Multiple Sequence Similarities Calculation Using a Low Complexity Method

An Efficient Parallel Algorithm for Multiple Sequence Similarities Calculation Using a Low Complexity Method

... In this work, we presented a parallel strategy to calculate sim- ilarities between multiple pairs of sequences using the k-mers couting method, a low computational complexity method with good biological ... See full document

7

Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform.

Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform.

... Limitations of this study should also be mentioned. First, the tonometer (PDS-2000) we applied in this study records only the two-dimensional data (pressure-time) of the pulse. Since more advanced instruments now ... See full document

20

Driver drowsiness detection: a comparison between intrusive and non-intrusive signal acquisition methods

Driver drowsiness detection: a comparison between intrusive and non-intrusive signal acquisition methods

... From the gaze direction measures, 3 features were extracted: the mean and standard deviation of the combined yaw and pitch gaze angles as well as the total fixation time. Several fixation segmentation algorithms are ... See full document

6

Modeling of very low frequency (VLF) radio wave signal profile due to solar flares using the GEANT4 Monte Carlo simulation coupled with ionospheric chemistry

Modeling of very low frequency (VLF) radio wave signal profile due to solar flares using the GEANT4 Monte Carlo simulation coupled with ionospheric chemistry

... The VLF receivers at the Indian Centre for Space Physics (ICSP) are continuously monitoring several worldwide VLF transmitter signals including NWC (19.8 kHz), VTX (18.2 kHz) and JJI (22.2 kHz). We use the VLF data for ... See full document

10

Small Signal Modeling Of Controller For Statcom Used In Distribution System For Reactive Power Management

Small Signal Modeling Of Controller For Statcom Used In Distribution System For Reactive Power Management

... In this paper non-linear model of the STATCOM is linearized and the following strategies have been adopted . Hence, a small signal model is adopted here. Here, the grid voltage lags the fundamental component of ... See full document

10

Low-complexity user selection for rate maximization in MIMO broadcast channels with downlink beamforming

Low-complexity user selection for rate maximization in MIMO broadcast channels with downlink beamforming

... a low-complexity algorithm that finds a quasiorthogonal set of users that maximizes the system throughput for MIMO BC channels using linear ZFBF and nonlinear ZFDP beamforming ...and ... See full document

14

Low Complexity DCT-based DSC approach forHyperspectral Image Compression with Arithmetic Code

Low Complexity DCT-based DSC approach forHyperspectral Image Compression with Arithmetic Code

... Discrete cosine transform is a versatile tool in hyperspectral remote sensing which is utilized for various applications such data compression. DCT and SPIHT are the most widely used methods for compression of ... See full document

8

Analysis of Low Complexity Motion Estimation Algorithms for H.264 Video Compression Standard

Analysis of Low Complexity Motion Estimation Algorithms for H.264 Video Compression Standard

... computational complexity by reducing the candidates that are chosen for the comparison, based on the knowledge that the human eyes cannot perceive fast motion with full ... See full document

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