Performance Comparison of Sub Phonetic Model with Input Signal Processing

2006 ◽  
Vol 2 (7) ◽  
pp. 577-582 ◽  
Author(s):  
Dr.E. Ramaraj ◽  
E. Chandra
Keyword(s):  
Signal Processing ◽  
Input Signal ◽  
Performance Comparison

scholarly journals Effect of varying Number of Spacing between Antenna Elements, Snapshots, SNR on AP ML, AP-SSF and ESPRIT Algorithm

2021 ◽  
Vol 11 ◽  
pp. 143-150
Author(s):  
Vinod Kumar ◽  
Sanjeev Kumar Dhull
Keyword(s):  
Signal Processing ◽  
Maximum Likelihood ◽  
Key Words ◽  
Array Signal Processing ◽  
Direction Of Arrival ◽  
Performance Comparison ◽  
Direction Of Arrival Estimation ◽  
Multiple Sources ◽  
Alternating Projection ◽  
Esprit Algorithm

The direction of arrival estimation is the main key problem in array signal processing. In this paper, the alternating projection maximum Likelihood (AP-ML), Alternating projection sub space framework (APSSF) and ESPRIT algorithm are studied. The simulation is performed in MATLAB for single and multiple sources. The effect of the varying number of spacing between antenna elements, number of snapshots and SNR are studied. The performance comparison shows that ESPRIT algorithm performs better as compared to the AP-ML and AP-SSF. Key-Words: - AP-ML, AP-SSF, Direction of Arrival, ESPRIT, Snapshots, SNR

scholarly journals Prototyping a System for Truck Differential Lock Control

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3619 ◽  
Author(s):  
Pavel Kučera ◽  
Václav Píštěk
Keyword(s):  
Signal Processing ◽  
Input Signal ◽  
Control Algorithm ◽  
Main Part ◽  
Proper Function ◽  
Mechatronic System ◽  
Important Benefit ◽  
Differential Lock ◽  
The Many ◽  
Prototype Testing

The article deals with the development of a mechatronic system for locking vehicle differentials. An important benefit of this system is that it prevents the jamming of the vehicle in difficult adhesion conditions. The system recognizes such a situation much sooner than the driver and is able to respond immediately, ensuring smooth driving in off-road or snowy conditions. This article describes the control algorithm of this mechatronic system, which is designed for firefighting, military, or civilian vehicles with a drivetrain configuration of up to 10 × 10, and also explains the input signal processing and the control of actuators. The main part of this article concerns prototype testing on a vehicle. The results are an evaluation of one of the many experiments and monitor the proper function of the developed mechatronic system.

A Humidity Measurement Method Based on Comb-Shaped Sensor

2013 ◽  
Vol 325-326 ◽  
pp. 827-831
Author(s):  
Xuan Zhe Wang ◽  
Man Man Liu ◽  
Shan Ting Ding ◽  
Hao Wei Wang
Keyword(s):  
Signal Processing ◽  
Input Signal ◽  
Measurement Method ◽  
Capacitive Sensor ◽  
Corrosion Monitoring ◽  
Atmospheric Humidity ◽  
Humidity Measurement ◽  
Noise Impact ◽  
Humidity Monitoring ◽  
Important Significance

Humidity measurement is an important link of corrosion monitoring in aircrafts and tanks. But the traditional monitor systems are not portable, can’t be real-time monitoring and other shortcomings. In order to solve these problems, a method that using a new sensor -- comb-shaped capacitive sensor in the humidity monitoring has been proposed. This method is based on electrical theory, combined with the processing of circuit, including the generation of the input signal, signal processing, and acquisition of output signal, and finally analyze the data collected to achieve the purpose of the monitoring of humidity.The problem of how to reduce the noise impact, how to simplify the theoretical calculation and other problems are considered and resolved in the design of the system.Compared with the traditional methods, the system based on this method is simple and compact because of its simple on the hardware design and the characteristics of the sensor. The experimental results show that this method has an very important significance in the atmospheric humidity monitoring.

Discrete Electronic Warfare Signal Processing using Compressed Sensing Based on Random Modulator Pre-Integrator

2015 ◽  
Vol 65 (6) ◽  
pp. 472 ◽  
Author(s):  
M. Sreenivasa Rao ◽  
Chandan C. Mishra ◽  
K. Krishna Naik ◽  
K. Maheshwara Reddy
Keyword(s):  
Signal Processing ◽  
Input Signal ◽  
High Speed ◽  
Traditional Approach ◽  
Ultra Wideband ◽  
Radar Signal ◽  
Electromagnetic Spectrum ◽  
Electronic Warfare ◽  
High Speed Adc ◽  
Detection Of Signals

Electronic warfare receiver works in the wide electromagnetic spectrum in dense radar signal environment. Current trends in radar systems are ultra wideband and low probability of intercept radar technology. Detection of signals from various radar stations is a concern. Performance and probability of intercept are mainly dependent on high speed ADC technology. The sampling and reconstruction functions have to be optimized to capture incoming signals at the receiver to extract characteristics of the radar signal. The compressive sampling of the input signal with orthonormal base vectors, projecting the basis in the union of subspaces and recovery through convex optimisation techniques is the current traditional approach. Modern trends in signal processing suggest the random modulator pre-integrator (RMPI), which sample the input signal at information rate non-adaptively and recovery by the processing of discrete and finite vectors. Analysis of RMPI theory, application to EW receiver, simulation and recovery of EW receiver signals are discussed.

scholarly journals Monitor for Anti-Aircraft Guidance and Observation Systems

2019 ◽  
Vol 10 (2) ◽  
pp. 143-150
Author(s):  
Rafał KRUK ◽  
Zbigniew REMPAŁA
Keyword(s):  
Signal Processing ◽  
Graphics Processing Units ◽  
General Purpose ◽  
Performance Comparison ◽  
Digital Data ◽  
Data Filtering ◽  
Observation Systems ◽  
Signal Processing Algorithms ◽  
Processing Algorithms ◽  
Graphics Processing

The paper presents a discussion on the issue of possible acceleration of radiolocation signal processing algorithms in seekers using graphics processing units. A concept and implementation examples of algorithms performing digital data filtering on general purpose central and graphics processing units are introduced. The results of performance comparison of central and graphics processing units during computing discrete convolution are presented at the end of the paper.

scholarly journals THE USE OF DIGITAL SIGNAL PROCESSING AND A NEURAL NETWORK WHEN GENERATING A FORECAST OF TIME SERIES OF DATA FOR THE PURPOSE OF DETECTING ANOMALIES IN THE IN THE AUTOMATED CONTROL OF TECHNOLOGICAL PROCESSES

2020 ◽  
Vol 20 (1) ◽  
pp. 24-34
Author(s):  
A. N. Ragozin ◽  
Keyword(s):  
Neural Network ◽  
Signal Processing ◽  
Digital Signal Processing ◽  
Input Signal ◽  
Forecast Error ◽  
Digital Signal ◽  
Processing Unit ◽  
Automated Control ◽  
Prediction Result ◽  
Low Pass

n order to detect anomalies and improve the quality of forecasting dynamic data flows observed from sensors in Industrial Control System (ACS)., it is proposed to use a predictive mod-ule consisting of a series-connected digital signal processing unit (DSP) and a predictive unit using a neural network (predictive autoencoder ( Auto Encoder), predictive Autoencoder (PAE)). The study showed that the preliminary DSP block of the predicted input signal, consisting of a parallel set (comb) of digital low-pass filters with finite impulse responses (FIR-LPF), leads to a non-equilibrium account of the correlation relationships of the time samples of the input signal and to increase the accuracy of the final prediction result. The predicted autoencoder (PAE) pro-posed and considered in the work, in addition to restoring the input signal or part of the input signal at the PAE output, also generates the predicted samples of the input signal for the speci-fied number of «forward» time steps at the output, which increases the accuracy of the predic-tion result. The reduction of the forecast error occurs due to the imposition of restrictions in the formation of the forecast, that is, an additional requirement to restore the input samples of the samples – «stabilizers» at the NS output. The introduction of «stabilizers» increases the accuracy of the prediction result.

scholarly journals Acceleration of Signal Processing Algorithms in Seekers Using Graphics Processing Units

2019 ◽  
Vol 10 (1) ◽  
pp. 91-98
Author(s):  
Piotr TUREK
Keyword(s):  
Signal Processing ◽  
Graphics Processing Units ◽  
General Purpose ◽  
Performance Comparison ◽  
Digital Data ◽  
Data Filtering ◽  
Discrete Convolution ◽  
Signal Processing Algorithms ◽  
Processing Algorithms ◽  
Graphics Processing

The paper presents a discussion on the issue of possible acceleration of radiolocation signal processing algorithms in seekers using graphics processing units. A concept and implementation examples of algorithms performing digital data filtering on general purpose central and graphics processing units are introduced. The results of performance comparison of central and graphics processing units during computing discrete convolution are presented at the end of the paper.

Comparison of Automated Acoustic Methods for Oral Diadochokinesis Assessment in Amyotrophic Lateral Sclerosis

2020 ◽  
Vol 63 (10) ◽  
pp. 3453-3460
Author(s):  
Michal Novotny ◽  
Jan Melechovsky ◽  
Kriss Rozenstoks ◽  
Tereza Tykalova ◽  
Petr Kryze ◽  
...  
Keyword(s):  
Signal Processing ◽  
Amyotrophic Lateral Sclerosis ◽  
Deep Learning ◽  
Performance Comparison ◽  
Accuracy Rate ◽  
Syllable Repetition ◽  
Wide Range ◽  
Als Patients ◽  
Oral Diadochokinesis ◽  
Lateral Sclerosis

Purpose The purpose of this research note is to provide a performance comparison of available algorithms for the automated evaluation of oral diadochokinesis using speech samples from patients with amyotrophic lateral sclerosis (ALS). Method Four different algorithms based on a wide range of signal processing approaches were tested on a sequential motion rate /pa/-/ta/-/ka/ syllable repetition paradigm collected from 18 patients with ALS and 18 age- and gender-matched healthy controls (HCs). Results The best temporal detection of syllable position for a 10-ms tolerance value was achieved for ALS patients using a traditional signal processing approach based on a combination of filtering in the spectrogram, Bayesian detection, and polynomial thresholding with an accuracy rate of 74.4%, and for HCs using a deep learning approach with an accuracy rate of 87.6%. Compared to HCs, a slow diadochokinetic rate ( p < .001) and diadochokinetic irregularity ( p < .01) were detected in ALS patients. Conclusions The approaches using deep learning or multiple-step combinations of advanced signal processing methods provided a more robust solution to the estimation of oral DDK variables than did simpler approaches based on the rough segmentation of the signal envelope. The automated acoustic assessment of oral diadochokinesis shows excellent potential for monitoring bulbar disease progression in individuals with ALS.

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