scholarly journals A Novel Hybrid Adaptive Filter to Improve Video Keyframe Clustering to Support Event Resolution in Cricket Videos

2019 ◽  
Vol 8 (6S3) ◽  
pp. 22-30
Keyword(s):  
Adaptive Filtering ◽  
Adaptive Filter ◽  
Video Summarization ◽  
Image Clustering ◽  
End Points ◽  
Different Types ◽  
Event Clustering ◽  
Sports Videos ◽  
Novel Algorithm

Automated summary generation of sports videos poses many challenges of detecting exciting events of a game. In our research, we focus on the table of content-based video summarization for cricket videos to facilitate efficient indexing of cricket events. Initially, we have identified event boundaries accurately to detect the event start and end points. To distinguish the different types of events, we need to analyze the sequence of the camera focus area. By observing the characteristics, we have categorized the camera focus area into several categories. To overcome the challenge of low accuracy we have introduced a novel algorithm for adaptive filtering for the comparison of hue histogram. The results prove that this algorithm is sufficient for accurate image clustering and this may be used in other sports event clustering as well.

scholarly journals Enhancing spatial perception through sound: mapping human movements into MIDI

2021 ◽  
Author(s):  
Bernardo Breve ◽  
Stefano Cirillo ◽  
Mariano Cuofano ◽  
Domenico Desiato
Keyword(s):  
Real Time ◽  
User Study ◽  
Spatial Perception ◽  
Human Movements ◽  
Different Types ◽  
Real Time Tracking ◽  
People’S Perceptions ◽  
Novel Algorithm

AbstractGestural expressiveness plays a fundamental role in the interaction with people, environments, animals, things, and so on. Thus, several emerging application domains would exploit the interpretation of movements to support their critical designing processes. To this end, new forms to express the people’s perceptions could help their interpretation, like in the case of music. In this paper, we investigate the user’s perception associated with the interpretation of sounds by highlighting how sounds can be exploited for helping users in adapting to a specific environment. We present a novel algorithm for mapping human movements into MIDI music. The algorithm has been implemented in a system that integrates a module for real-time tracking of movements through a sample based synthesizer using different types of filters to modulate frequencies. The system has been evaluated through a user study, in which several users have participated in a room experience, yielding significant results about their perceptions with respect to the environment they were immersed.

An Improved Adaptive Algorithm for INS/GPS System

2013 ◽  
Vol 397-400 ◽  
pp. 1606-1610 ◽  
Author(s):  
Li Dong Wang ◽  
Ying Zhao ◽  
Ni Zhang
Keyword(s):  
Adaptive Filtering ◽  
Adaptive Filter ◽  
Adaptive Algorithm ◽  
Initial Conditions ◽  
Forgetting Factor ◽  
Kalman Filter Algorithm ◽  
Simulation Results ◽  
The Stability ◽  
Gps System

In INS/GPS system, the changing of initial conditions and the quality of the data can affect the convergence of the conventional Kalman filter algorithm. Sage-Husa adaptive filter algorithm is adopted in the INS/GPS system in this paper. The effecting of the forgetting factor to the improved Sage-Husa adaptive filter algorithm is studied and the simulation results show that when the forgetting factor taken near 0.97, the adaptive filtering result is best, the stability of the system is guaranteed and the convergent speed of error can be reduced.

A New Variable Step Size LMS Adaptive Filtering Algorithm and its Analysis

2012 ◽  
Vol 605-607 ◽  
pp. 2193-2196
Author(s):  
Wei Ju Cai
Keyword(s):  
Adaptive Filtering ◽  
Functional Relationship ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Nonlinear Functional ◽  
Filtering Algorithm ◽  
Variable Step ◽  
Novel Algorithm ◽  
Better Than

The paper proposed a modified LMS algorithm of variable step size based on a brief analysis of traditional LMS,variable step size LMS algorithm and its improved algorithm.The novel algorithm based on nonlinear functional relationship between the step-size and the error ,increases adaptively at the beginning of the algorithm or when the channel is varying with time ,and it would be smaller during the steady state.So the algorithm has the excellences of faster constringency,little steady error ,tracking the change of the system and avoiding the effects of the noise. The theoretical analysis and computer simulation prove that the algorithm is better than traditional LMS algorithm.

scholarly journals Construction and Analysis of Integral User-Oriented Trustworthiness Metrics

Electronics ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 234
Author(s):  
Evgenia Novikova ◽  
Elena Doynikova ◽  
Diana Gaifulina ◽  
Igor Kotenko
Keyword(s):  
Information Systems ◽  
Risk Score ◽  
Reliability Level ◽  
Equal Importance ◽  
Different Types ◽  
Series Of Experiments ◽  
Novel Algorithm

Trustworthiness metrics help users to understand information system’s or a device’s security, safety, privacy, resilience, and reliability level. These metrics have different types and natures. The challenge consists of the integration of these metrics into one clear, scalable, sensitive, and reasonable metric representing overall trustworthiness level, useful for understanding if the users can trust the system or for the comparison of the devices and information systems. In this research, the authors propose a novel algorithm for calculation of an integral trustworthiness risk score that is scalable to any number of metrics, considers their criticality, and does not perform averaging in a case when all metrics are of equal importance. The obtained trustworthiness risk score could be further transformed to trustworthiness level. The authors analyze the resulting integral metric sensitivity and demonstrate its advantages on the series of experiments.

scholarly journals Efficient implementation of the third order RLS adaptive Volterra filter

2006 ◽  
Vol 19 (1) ◽  
pp. 133-141 ◽  
Author(s):  
Georgeta Budura ◽  
C. Botoca
Keyword(s):  
System Identification ◽  
Nonlinear System ◽  
Adaptive Filtering ◽  
Adaptive Filter ◽  
Nonlinear System Identification ◽  
Third Order ◽  
Volterra Filter ◽  
The Third ◽  
Nonlinear Adaptive Filtering ◽  
Made In

Nonlinear adaptive filtering techniques are widely used for the nonlinearities identification in many applications. This paper proposes a new implementation of the third order RLS Volterra filter based on the decomposition of the input vector. Its performances are evaluated in a typical nonlinear system identification application. Different degrees of nonlinearity for the nonlinear system are considered. Comparations, based on the adaptive filter error, are made in all cases with a linear identifier. The experimental results show that the proposed nonlinear identifier has better performances than the linear one.

scholarly journals A High-Robust Automatic Reading Algorithm of Pointer Meters Based on Text Detection

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5946
Author(s):  
Zhu Li ◽  
Yisha Zhou ◽  
Qinghua Sheng ◽  
Kunjian Chen ◽  
Jian Huang
Keyword(s):  
Adaptive Detection ◽  
Test Results ◽  
Linear Scale ◽  
Distance Method ◽  
Circular Arc ◽  
Scale Line ◽  
Different Types ◽  
Efficient Measurement ◽  
Automatic Reading ◽  
Novel Algorithm

Automatic reading of pointer meters is of great significance for efficient measurement of industrial meters. However, existing algorithms are defective in the accuracy and robustness to illumination shooting angle when detecting various pointer meters. Hence, a novel algorithm for adaptive detection of different pointer meters was presented. Above all, deep learning was introduced to detect and recognize scale value text in the meter dial. Then, the image was rectified and meter center was determined based on text coordinate. Next, the circular arc scale region was transformed into a linear scale region by polar transform, and the horizontal positions of pointer and scale line were obtained based on secondary search in the expanded graph. Finally, the distance method was used to read the scale region where the pointer is located. Test results showed that the algorithm proposed in this paper has higher accuracy and robustness in detecting different types of meters.

Design and Implementation of an Adaptable Trickle Algorithm for Amelioration of RPL Usage in Internet of Things Networks

2021 ◽  
Vol 18 (4) ◽  
pp. 1186-1193
Author(s):  
J. N. V. R. Swarup Kumar ◽  
D. Suresh
Keyword(s):  
Internet Of Things ◽  
Low Power ◽  
Lossy Networks ◽  
Message Routing ◽  
Design And Implementation ◽  
Different Types ◽  
Simulation Results ◽  
Two Parameters ◽  
Novel Algorithm

The efficient message routing is highly challenging in terms of low power and lossy networks (loT) for transmission of data with overhead and delay. The protocols used for routing need to be designed such that they should be working efficiently. Efficiency in calculated in terms of energy and delivery of packets. RPL protocol is also designed with the aim of making these two parameters efficient. Even then it contains drawbacks. Trickle algorithm is designed with a goal to reduce the drawbacks in RPL. Trickle algorithm is used in RPL protocols for creation of routes between nodes in the network with different intervals. Unfortunately, there exists some more downsides for the trickle algorithm, which made design of several algorithms inorder to analyse different drawbacks. In this paper, on analysing different types of trickle algorithms and locating the drawback in every algorithm, a novel algorithm is designed which helps in reduction of the drawbacks that are found. The description of this algorithm along with the simulation results done using Cooja 3.0 simulator is also discussed in this paper. The Simulation of the algorithm that is newly designed is done by assuming a network with different count of nodes and comparing the results with the previously introduced Trickle algorithms.

Wavelet-Based Neural Network Adaptive Filter for sEMG Denoising

2011 ◽  
Vol 121-126 ◽  
pp. 4259-4264 ◽  
Author(s):  
Jian Hui Wang ◽  
Na Chen ◽  
Qian Xiao ◽  
Jian You Xu ◽  
Shu Sheng Gu
Keyword(s):  
Neural Network ◽  
Adaptive Filtering ◽  
Adaptive Filter ◽  
Distributed Storage ◽  
Hopfield Neural Network ◽  
Signal Denoising ◽  
Semg Signal ◽  
Filter Model ◽  
The Neural Network ◽  
Filtering Effect

For the large computation workload of the adaptive filter algorithm and the low filtering speed of the adaptive filter model based on wavelet transform, a wavelet-based neural network adaptive filter model is constructed in this paper. As the neural network has the capacity of distributed storage and fast self-evolution, Hopfield neural network is used to implement adaptive filtering algorithm LMS, so as to increase the computing speed. The model applied to sEMG signal denoising can achieve a better filtering effect.

scholarly journals On adaptive filtering for high dimensional systems under parameter uncertainty and its application to satellite data assimilation in oceanography

2016 ◽  
Vol 13 (2) ◽  
pp. 18-40
Author(s):  
S, Hoàng ◽  
R. Baraille ◽  
O. Talagrand ◽  
X. Carton ◽  
P.De Mey
Keyword(s):  
Kalman Filter ◽  
Kalman Filtering ◽  
Adaptive Filtering ◽  
Adaptive Filter ◽  
High Efficiency ◽  
Ocean Model ◽  
Numerical Estimation ◽  
Oceanic Circulation ◽  
Error Statistics ◽  
Better Than

In this paper, the adaptive filtering theory, recently proposed and developed the authors of present work [1-9] for stochastic, encountered in the field of data as simulation in meteorology and oceanography, is reviewed. Several important questions on numerical estimation og the gain matrix, model reduction, structural  choices for the gain, filter stability… are discussed. We show the connections of present approach with a standard Kalman filtering. Adaptive filter is implemented along with a Kalman filtering. Adaptive filter is implemented along with a Kalman filter and standard Newton relation method on the four-layer adiabatic Miami Isopycnical Co-ordinate Ocean Model (MICOM) to produce the estimate for the deep oceanic circulation using assimilate synthetic observations of surface height. Numerical results justify high efficiency of the adaptive filter whose performance is slightly better than that of a Kalman filter due to  impossibility to correctly specify the error statistics in a Kalman filter.

scholarly journals Performance Analysis of Karatsuba Vedic Multiplier and Computation Sharing Multiplier in the Adaptive Filter Design

2019 ◽  
Vol 9 (2) ◽  
pp. 4425-4429
Keyword(s):  
Integrated Circuits ◽  
Adaptive Filtering ◽  
Adaptive Filter ◽  
Filter Design ◽  
Digital Signal ◽  
Vedic Multiplier ◽  
Lms Filter ◽  
Time Signals ◽  
Logic Operations ◽  
Computation Sharing

As real time signals change continuously, adaptive filtering is required for noise cancellation. An adaptive filter is one whose characteristics can be modified by adjusting its parameters according to an optimization algorithm The adaptive filtering operations can be implemented as a sequence of logic operations on a Digital Signal Processing (DSP) chip,Gate Arrays such as FPGA or Application Specific Integrated Circuits. There is always a tradeoff in the parameters area, power and speed in VLSI. This paper provides the implementation of adaptive LMS Filter using different types of multiplier and its analysis for the various parameters. The LMS Filter is designed using conventional array multiplier, Computation Sharing Mutliplier(CSHM) and Karatsuba Vedic Multiplier. The results show 70% reduction in delay and 19% reduction in area on using Karatsuba Vedic Multiplier ofr adaptive filter design.

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