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Data Analysis Articles
Page 3 of 18
Implementation of Fourier Series up to \"n\" Harmonics in MATLAB
In mathematics, the Fourier series up to "n" harmonics is a technique used to approximate a periodic function through the sum of sine and cosine functions. We can implement the Fourier series up to "n" harmonics in MATLAB programming. Before discussing this implementation, let us first get an overview of Fourier series up to "n" harmonics. What is Fourier Series up to "n" Harmonics? In mathematics, the Fourier series is a method of expressing a periodic function as a sum of sinusoidal functions (sine and cosine functions). The Fourier series up to "n" harmonics is a way of approximating a ...
Read MoreImplementation of Cayley-Hamilton\'s Theorem in MATLAB
In linear algebra, there is a fundamental theorem caled Cayley-Hamilton’s Theorem that is used to establish a relation between a square matrix and its characteristic equation. Read this article to learn the implementation of the Cayley-Hamilton’s theorem in MATLAB programming. Let's start with an overview of Cayley-Hamilton’s theorem. What is Cayley-Hamilton’s Theorem? In linear algebra, the Cayley-Hamilton’s theorem is a fundamental theorem that is used to establish a relationship between a square matrix and its characteristic equation. In other words, according Cayley-Hamilton’s theorem, a square matrix must satisfy its own characteristic equation. Explanation Consider a square matrix A of the ...
Read MoreImage Sharpening Using Laplacian Filter and High Boost Filtering in MATLAB
In MATLAB, there are two commonly used image processing techniques namely, "Laplacian Filter" and "High Boost Filtering" that are used to sharpen an image. The Laplacian filter is mathematical operator used to sharpen an image in digital image processing. While, the high boost filtering is an image sharpening technique in digital image processing. In this tutorial, I will explain the process of image sharpening using Laplacian filter and high boost filtering in MATLAB. Let’s start with the basic introduction of Laplacian filter and high boost filtering. What is Laplacian Filter in MATLAB? In MATLAB, the Laplacian filter is mathematical tool ...
Read MoreHow to Swap Elements in a matrix Using MATLAB?
A matrix is a structure which is used to store and work with numeric data. Each value stored in a matrix is referred to as an element. Sometimes, we need to swap or change the position of these elements within the matrix. We can use MATLAB to perform this task i.e., swapping the elements of the matrix. In this tutorial, I will explain how we can use MATLAB to swap the elements in a matrix. Swap Elements in a Matrix MATLAB is a powerful tool that can be used to manipulate matrices. It provides various methods to swap the elements ...
Read MoreHow to Select Random Rows from a Matrix in MATLAB?
In MATLAB, we can perform various operations on matrices. One such operation is selecting random rows from a matrix. MATLAB provides several different methods of selecting random rows from a matrix. In this tutorial, I will explain different methods of selecting rows from a matrix randomly using MATLAB. Select Random Rows from a Matrix in MATALB In MATLAB, we have various built-in functions that can be used to randomly select rows from a matrix. The following are some commonly used functions to randomly select rows from a matrix − randperm() Function randsample() Function randi() Function datasample() Function Let ...
Read MoreHow to Round toward Negative Infinity in MATLAB?
Rounding toward negative infinity is a method of rounding a number "N" down to the nearest integer less than or equal to the number "N". This method is also called "flooring". In simple words, rounding a number toward negative infinity is a method of finding the largest integer number which is less than or equal to the given number. For example, consider a number 4.8, when this number is round to negative infinity. Then, it will become 4. This is because, 4 is the largest integer number less than or equal to 4.8. Similarly, if we have a negative ...
Read MoreThe Factorized Random Synthesizer (FRS)
Introduction Creating realistic artificial data has become increasingly important in recent years, thanks to the wealth of extensive datasets and advancements in machine learning techniques. Traditional methods like data enrichment and sampling fall short in accurately capturing the complexity and diversity of real-world situations. However, the Factorized Random Synthesizer (FRS) tackles these limitations head-on by combining factorization methods with randomization, enabling the production of top-notch synthetic data. Fundamentals of Factorization Techniques In the realm of machine learning, various methods, including factorization techniques, harness the power of data to reveal hidden patterns and representations. Matrix factorization, tensor factorization, and deep factorization ...
Read MoreWhat is Regularized Discriminant Analysis in Machine Learning?
RDA, or Regularized discriminant analysis, is a statistical method used in machine learning classification problems. It is a change that fixes problems faced with linear discriminant analysis (LDA). This article will discuss RDA, including its benefits, how it works, applications, and advantages. Linear Discriminant Analysis (LDA) LDA is a way to sort things into different groups by finding a linear set of features that can split two or more groups. It involves finding a way to map the data onto a place with fewer dimensions while keeping the distance between the classes as large as possible. LDA thinks that all ...
Read MoreProblem-solving on Boolean Model and Vector Space Model
Introduction In information retrieval and text analysis, solving problems is a vital part of finding the correct information from extensive collections of papers quickly and effectively. The Boolean and Vector Space Models are well-known models that offer different ways to solve problems. To improve knowledge retrieval processes, it is essential to understand these models and how they solve problems. Boolean Model The Boolean Model is a way to find information. It is based on Boolean logic about true and false numbers. This model shows documents and queries as sets of terms, where each term can be present (true) or missing ...
Read MoreHow to Remove Salt and Pepper Noise from Image Using MATLAB?
MATLAB is a digital tool that is widely used in image processing, such as image transformation, noise removal from an image, detecting edges, and more. In this tutorial, I will explain how you can remove salt and pepper noise from a digital image using MATLAB. In a digital image, the "salt and pepper noise" is a type of impulse noise that degrade the image quality and cause errors in image processing, analysis, and transmission. Therefore, it is important to remove the salt and pepper noise from the image to minimize the challenges coming to image processing and analysis. Before ...
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