In-phase and quadrature components are concepts commonly used in signal processing and telecommunications, particularly in the context of complex signals and modulation techniques. They allow for the effective representation and manipulation of signals in both analog and digital forms. 1. **In-Phase Component (I)**: This is the part of a signal that is aligned with the reference signal (often a cosine wave). It represents the component of the signal that follows the same phase as the reference.
A Low Frequency Analyzer and Recorder is a specialized instrument or device designed to capture, analyze, and record low-frequency signals, typically in the range of a few hertz up to several kilohertz. These devices are used in various fields, including geophysics, seismology, audio engineering, and electromagnetic research.
MUSHRA stands for "Multiple Stimuli with Hidden Reference and Anchor." It is a listening test used to evaluate the quality of audio codecs or audio processing algorithms. The primary purpose of MUSHRA is to provide a subjective assessment of audio quality by allowing listeners to compare multiple audio samples. In a typical MUSHRA test, participants are presented with several audio samples, which include: 1. **Hidden Reference**: A high-quality version of the audio that serves as a benchmark for quality.
Multitaper is a spectral analysis technique that is particularly effective for estimating the power spectrum of signals while reducing spectral leakage and improving frequency resolution. It is especially useful in analyzing time series data that may have noise or non-stationary characteristics. The method involves the use of multiple tapers, which are specific window functions designed to minimize spectral leakage.
Pairwise error probability is a statistical measure used in the context of communication and signal processing, specifically in the analysis of error performance of multi-class classification systems or communication channels. It quantifies the probability of making an incorrect decision between two specific classes or hypotheses.
Pulse-width modulation (PWM) is a technique used to encode a message into a pulsing signal. It involves varying the width of the pulses in a signal while keeping the frequency constant. This modulation method is commonly used in various applications, including controlling the power delivered to electronic devices, transmission of information, and generating analog signals.
Pulse width refers to the duration of time that a signal is in a "high" or "active" state during a pulse cycle. It is typically measured in seconds, milliseconds, microseconds, or nanoseconds, depending on the context. In digital electronics and signal processing, pulse width is an important parameter that characterizes the timing of digital signals, particularly in applications like pulse-width modulation (PWM), timers, and communication protocols.
Rasta filtering, also known as "Rasta" or "Rasta-based filtering," is a technique used primarily in the field of signal processing and telecommunications. It is particularly relevant for improving speech recognition accuracy in audio processing systems. The term "Rasta" itself derives from the name "Relative Spectral" filtering, and it refers to methods that focus on normalizing or adjusting the spectral characteristics of a signal in a time- and frequency-selective manner.
The term "return ratio" can refer to different financial metrics that assess the profitability or performance of an investment, company, or financial asset relative to its costs or capital. Here are a few common return ratios: 1. **Return on Investment (ROI)**: This ratio measures the gain or loss generated relative to the amount of money invested.
The Sensitivity Index is a measure used to quantify how sensitive a particular outcome is to changes in input variables. It is commonly employed in various fields such as finance, risk management, environmental studies, and epidemiology, among others. The concept helps analysts understand the impact of uncertainty in input variables on the final results of a model or system.
Signal reconstruction refers to the process of recovering a signal from a set of incomplete or corrupted data points, such as samples or measurements. This is a fundamental concept in various fields such as signal processing, communications, and data analysis. The aim is to accurately recreate the original signal from available information, often using mathematical algorithms and techniques.
Signal subspace refers to a conceptual framework used in signal processing, particularly in the context of dimensionality reduction, feature extraction, and various applications such as array signal processing, estimation, and machine learning. The idea is based on the notion that signals of interest reside in a lower-dimensional space (subspace) of the overall signal space.
A **signal transfer function** is a mathematical representation used in control systems and signal processing to describe the relationship between the input and output signals of a system. It simplifies the analysis of linear time-invariant (LTI) systems by using the Laplace transform or the Fourier transform. ### Basics of Transfer Function 1.
A spectrogram is a visual representation of the spectrum of frequencies in a signal as it varies with time. It is commonly used in various fields such as audio processing, speech analysis, music analysis, and signal processing. The spectrogram is generated by taking a time-domain signal and applying a Fourier transform to break it down into its frequency components over time. The result shows how the frequency content of the signal changes over time, typically with: - The horizontal axis representing time.
A time-invariant system is a system in which the behavior and characteristics do not change over time.
Time reversal signal processing is a technique used in various fields such as acoustics, optics, and telecommunications, which leverages the principles of wave propagation and symmetry in physical systems. The core idea behind time reversal is to capture and reconstruct a signal by effectively reversing the travel time of the waves that carry it.
A **Clifford semigroup** is a specific type of algebraic structure in the study of semigroups, particularly within the field of algebra. A semigroup is a set equipped with an associative binary operation. Specifically, a Clifford semigroup is defined as a commutative semigroup in which every element is idempotent.
A Turbo equalizer is a type of equalization technique used primarily in communication systems to improve the performance of data transmission over noisy channels. It combines turbo coding with equalization methods to effectively combat the effects of multipath fading and inter-symbol interference (ISI). Here’s a brief overview of its key components: 1. **Turbo Coding**: This refers to a class of error correction codes that use iterative decoding to approach the Shannon limit, which is the theoretical maximum efficiency of a communication channel.

Pinned article: Introduction to the OurBigBook Project

Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
We have two killer features:
  1. topics: topics group articles by different users with the same title, e.g. here is the topic for the "Fundamental Theorem of Calculus" ourbigbook.com/go/topic/fundamental-theorem-of-calculus
    Articles of different users are sorted by upvote within each article page. This feature is a bit like:
    • a Wikipedia where each user can have their own version of each article
    • a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
    This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.
    Figure 1.
    Screenshot of the "Derivative" topic page
    . View it live at: ourbigbook.com/go/topic/derivative
  2. local editing: you can store all your personal knowledge base content locally in a plaintext markup format that can be edited locally and published either:
    This way you can be sure that even if OurBigBook.com were to go down one day (which we have no plans to do as it is quite cheap to host!), your content will still be perfectly readable as a static site.
    Figure 5. . You can also edit articles on the Web editor without installing anything locally.
    Video 3.
    Edit locally and publish demo
    . Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension.
  3. https://raw.githubusercontent.com/ourbigbook/ourbigbook-media/master/feature/x/hilbert-space-arrow.png
  4. Infinitely deep tables of contents:
    Figure 6.
    Dynamic article tree with infinitely deep table of contents
    .
    Descendant pages can also show up as toplevel e.g.: ourbigbook.com/cirosantilli/chordate-subclade
All our software is open source and hosted at: github.com/ourbigbook/ourbigbook
Further documentation can be found at: docs.ourbigbook.com
Feel free to reach our to us for any help or suggestions: docs.ourbigbook.com/#contact