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Convergence of Fourier Series01:21

Convergence of Fourier Series

131
The Fourier series is a powerful mathematical tool for representing periodic signals as an infinite sum of complex exponentials. In practice, this infinite series is truncated to a finite number of terms, yielding a partial sum. This truncation makes the approximation of the signal feasible but introduces certain challenges, particularly near discontinuities, known as the Gibbs phenomenon.
The Gibbs phenomenon refers to the persistent oscillations and overshoots that occur near discontinuities...
131
Region of Convergence01:17

Region of Convergence

394
The z-transform is a powerful mathematical tool used in the analysis of discrete-time signals and systems. It is a crucial tool in the analysis of discrete-time systems, but its convergence is limited to specific values of the complex variable z. This range of values, known as the Region of Convergence (ROC), is fundamental in determining the behavior and stability of a system or signal. The ROC defines the region in the complex plane where the z-transform converges, which can take various...
394
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

45
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
45
Fast Fourier Transform01:10

Fast Fourier Transform

281
The Fast Fourier Transform (FFT) is a computational algorithm designed to compute the Discrete Fourier Transform (DFT) efficiently. By breaking down the calculations into smaller, manageable sections, the FFT significantly reduces the computational complexity involved. Direct computation of an N-point DFT requires N2 complex multiplications, whereas the FFT algorithm needs only (N/2)log⁡2N multiplications, offering a much faster performance.
The computational efficiency of the FFT becomes...
281
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

358
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
358
Multimachine Stability01:25

Multimachine Stability

143
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
143

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Updated: Jun 11, 2025

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
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Disquisition on convergence, stability, and data dependence for a new fast iterative process.

A Murali1, K Muthunagai2

  • 1Vellore Institute of Technology, Chennai, India.

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A new iterative process rapidly approximates fixed points for contraction mappings. This method demonstrates superior convergence speed and stability compared to existing techniques.

Keywords:
Complex valued Banach spacesIterative processesM-Fast iterative processStability

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Area of Science:

  • Fixed-point theory
  • Numerical analysis
  • Functional analysis

Background:

  • Fixed-point iteration is crucial for solving equations.
  • Existing methods can be slow for certain mapping types.

Purpose of the Study:

  • Introduce a novel, fast iterative process.
  • Analyze convergence, stability, and efficiency.

Main Methods:

  • Developed a new iterative algorithm.
  • Proved theoretical convergence properties.
  • Conducted numerical simulations and comparisons.

Main Results:

  • The proposed iterative process shows strong convergence.
  • Demonstrated faster convergence than existing methods.
  • Established stability and dependence results.

Conclusions:

  • The novel iterative process is efficient and robust.
  • Offers a superior alternative for fixed-point approximation.
  • Enhances practical applications in relevant fields.