Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Linear Approximation in Time Domain

Linear Approximation in Time Domain

Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length, the...

Regression Toward the Mean

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...

Linear Approximation in Frequency Domain

Linear Approximation in Frequency Domain

Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear.

Regression Analysis

Regression Analysis

Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:

Drug Concentration Versus Time Correlation

Drug Concentration Versus Time Correlation

The plasma drug concentration-time curve is a crucial tool in pharmacokinetics, representing the drug's concentration in plasma at different time intervals post-administration. This curve illustrates the drug's journey from absorption into the systemic circulation, distribution to body tissues, and eventual elimination through excretion or biotransformation.
Two pivotal parameters are the minimum effective concentration (MEC) and the minimum toxic concentration (MTC). The MEC is the lowest drug...

Noncompartmental Analysis: Mean Residence Time

Noncompartmental Analysis: Mean Residence Time

According to statistical moment theory, mean residence time (MRT) is an important measure in pharmacokinetics. MRT can be defined as the expected mean of a probability density function distribution. It provides valuable insights into drug disposition in the body.
After the administration of a drug through intravenous bolus injection, the drug molecules are distributed throughout the body and remain there for varying periods. The MRT represents the average time these drug molecules stay in the...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Single-channel EEG captures tDCS-induced changes in neural reactivity: a pilot study in disorders of consciousness patients and healthy controls.

Therapeutic advances in neurological disorders·2026

Same author

Neural dissociation of cognitive effort and physiological arousal: Multimodal single-channel EEG, cortisol, and HRV evidence from an ecologically valid field study.

International journal of psychophysiology : official journal of the International Organization of Psychophysiology·2026

Same author

A benchmark for evaluating diagnostic questioning efficiency of LLMs in patient conversations.

Scientific reports·2026

Same author

Evaluating cognitive decline detection in aging populations with single-channel EEG features based on two studies and meta-analysis.

Scientific reports·2025

Same author

Pre-hospital stroke monitoring past, present, and future: a perspective.

Frontiers in neurology·2024

Same author

Evaluation of Parkinson's disease early diagnosis using single-channel EEG features and auditory cognitive assessment.

Frontiers in neurology·2024

Search research articles

Related Experiment Video

Updated: May 19, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

Semi-coherent time of arrival estimation using regression.

Alexander Apartsin¹, Leon N Cooper, Nathan Intrator

¹Blavatnik School of Computer Science, Tel-Aviv University, Ramat-Aviv 69978, Israel. apartzin@tau.ac.il

The Journal of the Acoustical Society of America

|August 17, 2012

Summary

This study introduces a novel biosonar-inspired method for time of arrival (ToA) estimation in noisy conditions. The new technique outperforms traditional methods when receivers operate in a semi-coherent state, improving accuracy in remote sensing applications.

Related Experiment Videos

Last Updated: May 19, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

Area of Science:

Signal Processing
Remote Sensing
Acoustics

Background:

Time of arrival (ToA) estimation is crucial for radar, sonar, and underground exploration.
The standard maximum likelihood estimator (MLE) for ToA suffers accuracy degradation in high noise environments due to the threshold effect.
Conventional methods often assume coherent receivers, which is unsuitable for semi-coherent states common in noisy applications.

Purpose of the Study:

To develop a robust ToA estimation method for semi-coherent receivers operating under noisy conditions.
To address the limitations of the conventional MLE in the presence of the threshold effect.
To introduce a biosonar-inspired approach for improved ToA estimation accuracy.

Main Methods:

The proposed method utilizes multiple phase-shifted unmatched filters instead of a single matched filter.
Each unmatched filter provides a biased ToA estimator.
A regression technique is employed to combine these biased estimators into a single, unbiased ToA estimator.

Main Results:

The biosonar-inspired method demonstrates superior performance compared to the MLE in semi-coherent states with significant noise.
The regression-based combination of biased estimators effectively mitigates the threshold effect.
The developed technique offers enhanced accuracy for ToA estimation in challenging remote sensing scenarios.

Conclusions:

The novel biosonar-inspired method provides a more accurate and robust solution for semi-coherent ToA estimation than conventional MLE.
This approach effectively overcomes the limitations of existing methods in high-noise environments.
The findings have significant implications for improving the performance of various remote sensing systems.