Electronics noise
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Noise is always present in electronic systems due to fluctuations in the atomic structure of components. There are several common types of noise including thermal noise caused by heat from random atom movement, flicker noise from random charge carrier variations, and shot noise from uneven charge distributions. The signal-to-noise ratio is used to quantify signal quality and is the ratio of signal power to noise power expressed in decibels, with a higher ratio indicating less noise corruption of the signal.
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Microphones convert sound waves into electrical signals by using a diaphragm that vibrates when hit by sound waves. This vibration is then converted into a varying electrical current through different mechanisms depending on the microphone type. The main types are dynamic, condenser and ribbon microphones. Microphones can also be classified by their directional properties and application.
Microphone types and characteristics essay
The document summarizes the history and types of microphones. It describes how the first microphone was invented in 1876 and key developments like the ribbon microphone in 1931 and electric microphone in 1964. It then explains how microphones work by transforming sound waves into electrical signals. The main types of microphones are described - dynamic, condenser, ribbon, carbon, crystal - along with their characteristics. Polar patterns like omni-directional, bi-directional and cardioid are also covered. The document concludes by discussing the purpose of different microphones and their appropriate uses.
Microphone
Microphone is a type of acoustic transducer or sensor.
A microphone, is an acoustic-to-electrical transducer or sensor that converts sound in air into an electrical signal.
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Similar to Electronics noise
Noise
Noise is an unwanted random fluctuation in an electrical signal that is inherent in all electronic systems. There are two main types of noise: internal noise generated within components like thermal noise and shot noise, and external noise from outside sources such as atmospheric noise. Noise can have detrimental effects on signal quality and effective communication, so techniques are used to quantify noise levels and maximize the signal-to-noise ratio.
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Noise is any unwanted signal that interferes with the desired signal. There are two main categories of noise - interference from human-made sources and naturally occurring random noise. Naturally occurring noise comes from atmospheric disturbances, solar noise, cosmic noise, and thermal noise within electronic components. Thermal noise arises from the random movement of electrons in conductors and follows Johnson's and Nyquist's laws. Shot noise results from the random arrival of charge carriers. Flicker noise is a low frequency noise that follows a 1/f relationship. Receiver noise comes from internal components and includes thermal noise, shot noise, partition noise, and avalanche noise. The signal-to-noise ratio is a measure of the desired signal strength relative to the
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Electrical noise is any undesirable electrical energy within a signal's pass band. There are several types of noise including man-made, thermal, correlated, and impulse noise. Man-made noise comes from sources like electric motors and lights. Thermal noise results from random electron motion and increases with temperature. Correlated noise is noise related to the signal, like harmonic distortion from nonlinear amplification. Impulse noise consists of short, high amplitude bursts from sources such as electric motors or lightning.
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This document discusses different types of noise in communication systems. It defines noise and describes two main categories of noise: external noise and internal noise. External noise sources include atmospheric noise from lightning, extraterrestrial noise from space objects, and man-made noise from industrial equipment. Internal noise is generated within communication systems and includes thermal noise, shot noise, flicker noise, and intermodulation noise caused by non-linear components. The document provides detailed explanations and examples of different noise sources.
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The document discusses various sources and types of noise in communication systems and instrumentation. It provides details on fundamental, environmental, and instrumental noise. The major types of fundamental noise are thermal, shot, and flicker noise. Thermal noise originates from thermally induced motions in charge carriers and is represented by a formula involving resistance, temperature, and bandwidth. Shot noise arises when current involves the movement of charged particles across a junction, like at a pn interface. Flicker noise is associated with crystal surface defects and decreases with increasing frequency. Hardware techniques for improving signal-to-noise ratio include filtering, grounding/shielding, difference amplifiers, and analog filtering. Narrowing bandwidth and lowering resistance/temperature can reduce thermal noise
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The signal is the meaningful information that you’re actually trying to detect. The noise is the random, unwanted variation or fluctuation that interferes with the signal. To get a sense of this, imagine trying to tune into a radio station. Ok, you don’t use radio anymore, so imagine your dad can’t call you to get help setting up his Spotify, so is trying to tune into a radio station. He turns the dial but it’s just picking up white noise and, after a few frustrating minutes, he manages to pick up a signal and tune into a station.
The same is true in statistics — there is something you’re trying to actually measure (say, how many Americans want to leave for Canada), but the data could be noisy (by including everyone who just makes a trip over the border to buy affordable medication). Noisy data are data from which it is hard to determine the true effect.Examples of signal vs noise
If I speak German, for most people, there will be no signal, just noise, although Claus can detect the actual signal.
How accurate are the polls in predicting the election? If the data are noisy (for example, because it’s a small sample size, has low external validity, or small effect size), the poll numbers won’t correlate well with a change in the chance of a different President.
Does money make you happier? The signal (correlation between income and happiness) would be noisy because of confounders — you’d expect people who earn more to be happier because they are in positions of higher social status, they have better working conditions, being happier could cause people to be rich etc. Turns out there is some signal amongst the noise though.
Noise in Electronic System
Noise is a fundamental parameter that limits performance in electronic systems. There are many sources of noise, both internal from components and external introduced into the circuit. The main types of internal noise discussed are Johnson noise (thermal noise) which is present in all conductors, shot noise from current flow across barriers, 1/f noise which increases at low frequencies, and photon noise from the quantum nature of radiation. Noise from these various sources adds depending on whether they are correlated or not. Noise is typically expressed as a noise spectral density and most common sources like Johnson noise exhibit white or frequency-independent noise.
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This document discusses different types of noise sources and noise theory concepts. It covers shot noise, thermal noise, and white noise. It also discusses noise equivalent temperature, narrowband noise representation, noise figure, signal-to-noise ratio (SNR), and noise in different communication systems using amplitude modulation (AM), frequency modulation (FM), and coherent/envelope detection. Key concepts summarized include noise figure determination, narrowband noise representation using in-phase and quadrature components, noise properties, and figures of merit for different modulation schemes in the presence of noise.
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The noise figure of the amplifier is given as 3.2 dB at an ambient temperature of 297K.
Using the formula:
Noise figure (dB) = 10log10(Noise factor)
3.2 dB = 10log10(F)
F = 10^(3.2/10) = 2.09
Noise equivalent temperature, Te = (F - 1)T
= (2.09 - 1)(297K)
= 323K
Therefore, the noise equivalent temperature of the amplifier is 323K.
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The document provides an overview of basic acoustics concepts including quantification of sound through measurements of sound pressure, intensity, and power. It discusses acoustic variables such as sound pressure level and intensity level which are expressed on a logarithmic decibel scale. Key concepts covered include the inverse square law describing how sound pressure/intensity decreases with distance from a point source, effects of multiple sound sources, relationships between frequency and sound perception, and directionality of sound sources. Measurement techniques and standards are also summarized.
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This document discusses techniques for enhancing the signal-to-noise ratio in analytical measurements. It describes what the signal-to-noise ratio is and explains common sources of noise like thermal noise, shot noise, and flicker noise. It then discusses various hardware and software methods for improving the SNR, such as shielding, grounding, difference amplifiers, filtering (low-pass, high-pass, band-pass), ensemble averaging, and moving averages. Modulation and lock-in amplifiers are also covered as techniques to extract low-level signals from noise.
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Electronics noise
- 1. NOISE Noise is always present within electronic systems and is due to fluctuations within the atomic structure of the components making up the system. Original digital signal Original analogue signal Original analogue signal with noise Original digital signal with noise Noise is not related to the input signal
- 2. COMMON TYPES of NOISE Thermal (Johnson) Noise: Caused by heat generated due to the random movement of atoms within the components. Has an infinite bandwidth with equal noise power. Flicker Noise: Caused by random variations in the diffusion of charge carriers within devices, transistors especially and is a low frequency noise. Shot Noise: Caused by uneven distribution of charge carriers due to the granular nature of semiconductor materials as a result of fluctuations in the diffusion process. Pink Noise: A low frequency noise similar to flicker noise also known as 1/f noise since its power spectrum is inversely proportional to frequency. White Noise: Similar to thermal noise, having noise components at all frequencies with equal noise power across the spectrum.
- 3. SIGNAL to NOISE RATIO The signal-to-noise ratio (S/N ratio) is a quantitative method of describing the quality of a signal in terms of its corruption by noise. That is, the ratio of the magnitude of the signal to that of the noise, usually expressed as the ratio of signal power (Ps) to the noise power (Pn). Ps S N ratio = 10 log10 Pn dB The signal-to-noise ratio within a given system varies with the magnitude of the signal. If the signal becomes very small, the relative size of the noise will increase causing the S/N ratio to decrease, (remember the noise level is independent of signal). Manufacturers of audio equipment often like to quote the signal-to-noise ratio as a selling point for their equipment.