Jitter Analysis
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Autoencoding Neural Networks As Musical Audio Synthesizers
Proceedings of the 21st International Conference on Digital Audio Effects (DAFx-18), Aveiro, Portugal, September 4–8, 2018 AUTOENCODING NEURAL NETWORKS AS MUSICAL AUDIO SYNTHESIZERS Joseph Colonel Christopher Curro Sam Keene The Cooper Union for the Advancement of The Cooper Union for the Advancement of The Cooper Union for the Advancement of Science and Art Science and Art Science and Art NYC, New York, USA NYC, New York, USA NYC, New York, USA [email protected] [email protected] [email protected] ABSTRACT This training corpus consists of five-octave C Major scales on var- ious synthesizer patches. Once training is complete, we bypass A method for musical audio synthesis using autoencoding neural the encoder and directly activate the smallest hidden layer of the networks is proposed. The autoencoder is trained to compress and autoencoder. This activation produces a magnitude STFT frame reconstruct magnitude short-time Fourier transform frames. The at the output. Once several frames are produced, phase gradient autoencoder produces a spectrogram by activating its smallest hid- integration is used to construct a phase response for the magnitude den layer, and a phase response is calculated using real-time phase STFT. Finally, an inverse STFT is performed to synthesize audio. gradient heap integration. Taking an inverse short-time Fourier This model is easy to train when compared to other state-of-the-art transform produces the audio signal. Our algorithm is light-weight methods, allowing for musicians to have full control over the tool. when compared to current state-of-the-art audio-producing ma- This paper presents improvements over the methods outlined chine learning algorithms. -
Application Note Template
correction. of TOI measurements with noise performance the improved show examples Measurement presented. is correction a noise of means by improvements range Dynamic explained. are analyzer spectrum of a factors the limiting correction. The basic requirements and noise with measurements spectral about This application note provides information | | | Products: Note Application Correction Noise with Range Dynamic Improved R&S R&S R&S FSQ FSU FSG Application Note Kay-Uwe Sander Nov. 2010-1EF76_0E Table of Contents Table of Contents 1 Overview ................................................................................. 3 2 Dynamic Range Limitations .................................................. 3 3 Signal Processing - Noise Correction .................................. 4 3.1 Evaluation of the noise level.......................................................................4 3.2 Details of the noise correction....................................................................5 4 Measurement Examples ........................................................ 7 4.1 Extended dynamic range with noise correction .......................................7 4.2 Low level measurements on noise-like signals ........................................8 4.3 Measurements at the theoretical limits....................................................10 5 Literature............................................................................... 11 6 Ordering Information ........................................................... 11 1EF76_0E Rohde & Schwarz -
Receiver Sensitivity and Equivalent Noise Bandwidth Receiver Sensitivity and Equivalent Noise Bandwidth
11/08/2016 Receiver Sensitivity and Equivalent Noise Bandwidth Receiver Sensitivity and Equivalent Noise Bandwidth Parent Category: 2014 HFE By Dennis Layne Introduction Receivers often contain narrow bandpass hardware filters as well as narrow lowpass filters implemented in digital signal processing (DSP). The equivalent noise bandwidth (ENBW) is a way to understand the noise floor that is present in these filters. To predict the sensitivity of a receiver design it is critical to understand noise including ENBW. This paper will cover each of the building block characteristics used to calculate receiver sensitivity and then put them together to make the calculation. Receiver Sensitivity Receiver sensitivity is a measure of the ability of a receiver to demodulate and get information from a weak signal. We quantify sensitivity as the lowest signal power level from which we can get useful information. In an Analog FM system the standard figure of merit for usable information is SINAD, a ratio of demodulated audio signal to noise. In digital systems receive signal quality is measured by calculating the ratio of bits received that are wrong to the total number of bits received. This is called Bit Error Rate (BER). Most Land Mobile radio systems use one of these figures of merit to quantify sensitivity. To measure sensitivity, we apply a desired signal and reduce the signal power until the quality threshold is met. SINAD SINAD is a term used for the Signal to Noise and Distortion ratio and is a type of audio signal to noise ratio. In an analog FM system, demodulated audio signal to noise ratio is an indication of RF signal quality. -
AN10062 Phase Noise Measurement Guide for Oscillators
Phase Noise Measurement Guide for Oscillators Contents 1 Introduction ............................................................................................................................................. 1 2 What is phase noise ................................................................................................................................. 2 3 Methods of phase noise measurement ................................................................................................... 3 4 Connecting the signal to a phase noise analyzer ..................................................................................... 4 4.1 Signal level and thermal noise ......................................................................................................... 4 4.2 Active amplifiers and probes ........................................................................................................... 4 4.3 Oscillator output signal types .......................................................................................................... 5 4.3.1 Single ended LVCMOS ........................................................................................................... 5 4.3.2 Single ended Clipped Sine ..................................................................................................... 5 4.3.3 Differential outputs ............................................................................................................... 6 5 Setting up a phase noise analyzer ........................................................................................................... -
Preview Only
AES-6id-2006 (r2011) AES information document for digital audio - Personal computer audio quality measurements Published by Audio Engineering Society, Inc. Copyright © 2006 by the Audio Engineering Society Preview only Abstract This document focuses on the measurement of audio quality specifications in a PC environment. Each specification listed has a definition and an example measurement technique. Also included is a detailed description of example test setups to measure each specification. An AES standard implies a consensus of those directly and materially affected by its scope and provisions and is intended as a guide to aid the manufacturer, the consumer, and the general public. An AES information document is a form of standard containing a summary of scientific and technical information; originated by a technically competent writing group; important to the preparation and justification of an AES standard or to the understanding and application of such information to a specific technical subject. An AES information document implies the same consensus as an AES standard. However, dissenting comments may be published with the document. The existence of an AES standard or AES information document does not in any respect preclude anyone, whether or not he or she has approved the document, from manufacturing, marketing, purchasing, or using products, processes, or procedures not conforming to the standard. Attention is drawn to the possibility that some of the elements of this AES standard or information document may be the subject of patent rights. AES shall not be held responsible for identifying any or all such patents. This document is subject to periodicwww.aes.org/standards review and users are cautioned to obtain the latest edition and printing. -
Noise Reduction by Cross-Correlation
Application Note Noise reduction by parallel Zurich cross-correlation measurements Instruments Applications: Nanoelectronics, Materials Characterization, Low-Temperature Physics, Transport Measurements, DC SQUID Products: MFLI, MFLI-DIG, MDS Release date: May 2019 Introduction 4 10 Studying noise processes can reveal fundamental infor- mation about a physical system; for example, its tem- perature [1, 2, 3],the quantization of charge carriers [4], 3 10 or the nature of many-body behavior [5]. Noise mea- surements are also critical for applications such as sensing, where the intrinsic noise of a detector defines its ultimate sensitivity. In this note, we will describe 100 a generic method for measuring the electronic noise of a device when the spectral density of its intrinsic noise is less than that of the measurement apparatus. 10 We implement the method using a pair of MFLI Lock-in Amplifiers, both with the Digitizer option MF-DIG. To demonstrate the measurement, we measure the 1 noise of a Superconducting Quantum Interference De- 100 101 102 103 104 105 106 vice (SQUID) magnetometer. Typically, SQUIDs are op- erated by supplying a DC bias current and measuring Figure 1. The voltage noise density at the Voltage Input of an MFLI a voltage and, as such, the limiting factor in the mea- Lock-in Amplifier plotted for available Input ranges [6]. surement is usually the noise floor of the voltage pre- amplifier. For a SQUID with gain (transfer function)p VΦ = 1 mV/Φ0 and targetp sensitivity of S = 1 μΦ0/ Hz, larly at low frequencies. One way of resolving signals a noise floor of 1 nV/ Hz is required. -
Uncovering Interference at a Co-Located 800 Mhz P25 Public Safety Communication System Case Study
Case Study Uncovering Interference at a Co-Located 800 MHz P25 Public Safety Communication System RTSA Spectrum Analyzer Key to Uncovering Hard-to-Find Cause Overview RF communication systems have become a critical part of modern life. These systems range from tiny Bluetooth® devices to nationwide, high-speed data systems to public safety critical infrastructure. Because these communication systems share common RF spectrum, interference between them is inevitable. Interference between systems can range from intermittent outages that can cause dropped calls to complete blockage of communication. Resolving these issues requires testing of the system with a test RF receiver or spectrum analyzer to detect and locate the source of interference within the system. 1 Challenge A public safety organization in northern Nevada was experiencing intermittent receive interference alarms on its 800 MHz P25 public safety communications system. An ordinary swept-tuned spectrum analyzer was used in an attempt to locate the interfering signals, however, none were found. After determining it was not a software issue, it was decided that the cause of the issue was likely to be an interfering signal with short duration or even a hopping signal that was being missed by the spectrum analyzer. A spectrum analyzer with real-time spectrum analysis (RTSA) was needed to be utilized to look for any interfering signals. Solution Anritsu’s Field Master Pro™ MS2090A solution with real-time spectrum analyzer option was selected to locate the interfering signal (Figure 1). The Field Master Pro MS2090A has an optional real-time mode that can accurately measure the amplitude of a single spectrum event as short as 2 µs, and detect a single event as short as 5 ns. -
AN-839 RMS Phase Jitter
RMS Phase Jitter AN-839 APPLICATION NOTE Introduction In order to discuss RMS Phase Jitter, some basics phase noise theory must be understood. Phase noise is often considered an important measurement of spectral purity which is the inherent stability of a timing signal. Phase noise is the frequency domain representation of random fluctuations in the phase of a waveform caused by time domain instabilities called jitter. An ideal sinusoidal oscillator, with perfect spectral purity, has a single line in the frequency spectrum. Such perfect spectral purity is not achievable in a practical oscillator where there are phase and frequency fluctuations. Phase noise is a way of describing the phase and frequency fluctuation or jitter of a timing signal in the frequency domain as compared to a perfect reference signal. Generating Phase Noise and Frequency Spectrum Plots Phase noise data is typically generated from a frequency spectrum plot which can represent a time domain signal in the frequency domain. A frequency spectrum plot is generated via a Fourier transform of the signal, and the resulting values are plotted with power versus frequency. This is normally done using a spectrum analyzer. A frequency spectrum plot is used to define the spectral purity of a signal. The noise power in a band at a specific offset (FO) from the carrier frequency (FC) compared to the power of the carrier frequency is called the dBc Phase Noise. Power Level of a 1Hz band at an offset (F ) dBc Phase Noise = O Power Level of the carrier Frequency (FC) A Phase Noise plot is generated using data from the frequency spectrum plot. -
Noise Measurement Post-Amp
Art Kay TI Precision Designs: Reference Design Noise Measurement Post-Amp TI Precision Designs Circuit Description TI Precision Designs are analog solutions created by In some cases a scope or spectrum analyzer does not TI’s analog experts. Reference Designs offer the have the range required to measure very small noise theory, component selection, and simulation of useful levels. This noise measurement post-amp boosts the circuits. Circuit modifications that help to meet output noise of the device under test (DUT) to allow alternate design goals are also discussed. for measurement with standard test equipment. The key requirements of this circuit is that it has a low noise floor and sufficient bandwidth for characterization of most devices. Design Resources Design Archive All Design files Ask The Analog Experts TINA-TI™ SPICE Simulator WEBENCH® Design Center OPA211 Product Folder TI Precision Designs Library OPA209 Product Folder OPA847 Product Folder DUT Post Amp Spectrum Rg 10 Rf 990 Vout_post Analyzer Vout_dut R3 10 R2 90 or -15V -2.5V Scope - C1 10u Vspect - ++ + M U2 OPA211 1 + U1 OPA376 1 R +15V +2.5V An IMPORTANT NOTICE at the end of this TI reference design addresses authorized use, intellectual property matters and other important disclaimers and information. TINA-TI is a trademark of Texas Instruments WEBENCH is a registered trademark of Texas Instruments TIDU016-December 2013-Revised December 2013 Noise Measurement Post Amp 1 Copyright © 2013, Texas Instruments Incorporated www.ti.com 1 Design Summary The design requirements are as follows: Supply Voltage: ±15 V, and ±2.5V Input: 0V (GND) Output: ac Noise Signal The design goals and performance are summarized in Table 1. -
Reducing ADC Quantization Noise
print | close Reducing ADC Quantization Noise Microwaves and RF Richard Lyons Randy Yates Fri, 20050617 (All day) Two techniques, oversampling and dithering, have gained wide acceptance in improving the noise performance of commercial analogtodigital converters. Analogtodigital converters (ADCs) provide the vital transformation of analog signals into digital code in many systems. They perform amplitude quantization of an analog input signal into binary output words of finite length, normally in the range of 6 to 18 b, an inherently nonlinear process. This nonlinearity manifests itself as wideband noise in the ADC's binary output, called quantization noise, limiting an ADC's dynamic range. This article describes the two most popular methods for improving the quantization noise performance in practical ADC applications: oversampling and dithering. Related Finding Ways To Reduce Filter Size Matching An ADC To A Transformer Tunable Oscillators Aim At Reduced Phase Noise LargeSignal Approach Yields LowNoise VHF/UHF Oscillators To understand quantization noise reduction methods, first recall that the signaltoquantizationnoise ratio, in dB, of an ideal Nbit ADC is SNRQ = 6.02N + 4.77 + 20log10 (LF) dB, where: LF = the loading factor measure of the ADC's input analog voltage level. (A derivation of SNRQ is provided in ref. 1.) Parameter LF is defined as the analog input rootmeansquare (RMS) voltage divided by the ADC's peak input voltage. When an ADC's analog input is a sinusoid driven to the converter's fullscale voltage, LF = 0.707. In that case, the last term in the SNRQ equation becomes −3 dB and the ADC's maximum output signaltonoise ratio is SNRQmax = 6.02N + 4.77 −3 = 6.02N + 1.77 dB. -
How to Evaluate Reference-Clock Phase Noise in High-Speed Serial Links
TECHNICAL FEATURE How to Evaluate Reference-Clock Phase Noise in High-Speed Serial Links Gary Giust SiTime ost high-speed serial-data 1a shows an example PLL whose phase detector communications standards do compares corresponding input and feedback not include specifications for edges, and outputs a pulse proportional to their reference-clock (refclk) jitter. phase difference, which is then filtered to control Instead, jitter is specified for a voltage-controlled oscillator. In this example, the serial-data signal, a portion the phase detector samples its inputs at their of which originates from the refclk. Thus, these rising-edge midpoints. Therefore, the average Mstandards limit refclk jitter indirectly. Such a sampling (FS) and input clock frequencies (FIN) scheme gives designers more freedom to choose are equal. refclks, and budget jitter accordingly. Spectral components of jitter located Traditionally, real-time oscilloscopes have above the Nyquist frequency (FS/2) alias, or been used to determine jitter compliance fold back, below the Nyquist frequency after in serial-data signals. This analysis is sampling. Figure 1b illustrates the PLL jitter- straightforward because an oscilloscope-based transfer function, whose lowpass filtering time-interval error (TIE) jitter measurement characteristic is mirrored across spectral observes jitter similar to an actual system, whose boundaries at integer multiples of the Nyquist jitter filtering may be emulated in software frequency, FS/2. Below the Nyquist frequency, executed in the oscilloscope. jitter frequencies falling inside the PLL loop On the other hand, clock-jitter analysis bandwidth pass unattenuated, whereas jitter traditionally derives jitter from a phase noise frequencies falling outside this bandwidth get analyzer due to its inherently lower instrument attenuated by the response of the loop. -
AN118: Improving ADC Resolution by Oversampling and Averaging
AN118 IMPROVING ADC RESOLUTION BY OVERSAMPLING AND AVERAGING 1. Introduction 2. Key Points Many applications require measurements using an Oversampling and averaging can be used to analog-to-digital converter (ADC). Such increase measurement resolution, eliminating the applications will have resolution requirements need to resort to expensive, off-chip ADCs. based in the signal’s dynamic range, the smallest Oversampling and averaging will improve the SNR and measurement resolution at the cost of increased change in a parameter that must be measured, and CPU utilization and reduced throughput. the signal-to-noise ratio (SNR). For this reason, Oversampling and averaging will improve signal-to- many systems employ a higher resolution off-chip noise ratio for “white” noise. ADC. However, there are techniques that can be 2.1. Sources of Data Converter Noise used to achieve higher resolution measurements and SNR. This application note describes utilizing Noise in ADC conversions can be introduced from oversampling and averaging to increase the many sources. Examples include: thermal noise, resolution and SNR of analog-to-digital shot noise, variations in voltage supply, variation in conversions. Oversampling and averaging can the reference voltage, phase noise due to sampling increase the resolution of a measurement without clock jitter, and noise due to quantization error. The resorting to the cost and complexity of using noise caused by quantization error is commonly expensive off-chip ADCs. referred to as quantization noise. Noise power from This application note discusses how to increase the these sources can vary. Many techniques that may resolution of analog-to-digital (ADC) measure- be utilized to reduce noise, such as thoughtful ments by oversampling and averaging.