Higher-Order Integrated Wavetable Synthesis
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Integer-Based Wavetable Synthesis for Low-Computational Embedded Systems Ben Wright and Somsak Sukittanon University of Tennessee at Martin Department of Engineering Martin, TN USA [email protected], [email protected] Abstract— The evolution of digital music synthesis spans from discussed. Section B will discuss the mathematics explaining tried-and-true frequency modulation to string modeling with the components of the wavetables. Part II will examine the neural networks. This project begins from a wavetable basis. music theory used to derive the wavetables and the software The audio waveform was modeled as a superposition of formant implementation. Part III will cover the applied results. sinusoids at various frequencies relative to the fundamental frequency. Piano sounds were reverse-engineered to derive a B. Mathematics and Music Theory basis for the final formant structure, and used to create a Many periodic signals can be represented by a wavetable. The quality of reproduction hangs in a trade-off superposition of sinusoids, conventionally called Fourier between rich notes and sampling frequency. For low- series. Eigenfunction expansions, a superset of these, can computational systems, this calls for an approach that avoids represent solutions to partial differential equations (PDE) burdensome floating-point calculations. To speed up where Fourier series cannot. In these expansions, the calculations while preserving resolution, floating-point math was frequency of each wave (here called a formant) in the avoided entirely--all numbers involved are integral. The method was built into the Laser Piano. Along its 12-foot length are 24 superposition is a function of the properties of the string. This “keys,” each consisting of a laser aligned with a photoresistive is said merely to emphasize that the response of a plucked sensor connected to 8-bit MCU. -
Lab 4: Using the Digital-To-Analog Converter
ECE2049 – Embedded Computing in Engineering Design Lab 4: Using the Digital-to-Analog Converter In this lab, you will gain experience with SPI by using the MSP430 and the MSP4921 DAC to create a simple function generator. Specifically, your function generator will be capable of generating different DC values as well as a square wave, a sawtooth wave, and a triangle wave. Pre-lab Assignment There is no pre-lab for this lab, yay! Instead, you will use some of the topics covered in recent lectures and HW 5. Lab Requirements To implement this lab, you are required to complete each of the following tasks. You do not need to complete the tasks in the order listed. Be sure to answer all questions fully where indicated. As always, if you have conceptual questions about the requirements or about specific C please feel free to as us—we are happy to help! Note: There is no report for this lab! Instead, take notes on the answers to the questions and save screenshots where indicated—have these ready when you ask for a signoff. When you are done, you will submit your code as well as your answers and screenshots online as usual. System Requirements 1. Start this lab by downloading the template on the course website and importing it into CCS—this lab has a slightly different template than previous labs to include the functionality for the DAC. Look over the example code to see how to use the DAC functions. 2. Your function generator will support at least four types of waveforms: DC (a constant voltage), a square wave, sawtooth wave, and a triangle wave, as described in the requirements below. -
Fourier Series
Chapter 10 Fourier Series 10.1 Periodic Functions and Orthogonality Relations The differential equation ′′ y + 2y = F cos !t models a mass-spring system with natural frequency with a pure cosine forcing function of frequency !. If 2 = !2 a particular solution is easily found by undetermined coefficients (or by∕ using Laplace transforms) to be F y = cos !t. p 2 !2 − If the forcing function is a linear combination of simple cosine functions, so that the differential equation is N ′′ 2 y + y = Fn cos !nt n=1 X 2 2 where = !n for any n, then, by linearity, a particular solution is obtained as a sum ∕ N F y (t)= n cos ! t. p 2 !2 n n=1 n X − This simple procedure can be extended to any function that can be repre- sented as a sum of cosine (and sine) functions, even if that summation is not a finite sum. It turns out that the functions that can be represented as sums in this form are very general, and include most of the periodic functions that are usually encountered in applications. 723 724 10 Fourier Series Periodic Functions A function f is said to be periodic with period p> 0 if f(t + p)= f(t) for all t in the domain of f. This means that the graph of f repeats in successive intervals of length p, as can be seen in the graph in Figure 10.1. y p 2p 3p 4p 5p Fig. 10.1 An example of a periodic function with period p. -
The Sonification Handbook Chapter 9 Sound Synthesis for Auditory Display
The Sonification Handbook Edited by Thomas Hermann, Andy Hunt, John G. Neuhoff Logos Publishing House, Berlin, Germany ISBN 978-3-8325-2819-5 2011, 586 pages Online: http://sonification.de/handbook Order: http://www.logos-verlag.com Reference: Hermann, T., Hunt, A., Neuhoff, J. G., editors (2011). The Sonification Handbook. Logos Publishing House, Berlin, Germany. Chapter 9 Sound Synthesis for Auditory Display Perry R. Cook This chapter covers most means for synthesizing sounds, with an emphasis on describing the parameters available for each technique, especially as they might be useful for data sonification. The techniques are covered in progression, from the least parametric (the fewest means of modifying the resulting sound from data or controllers), to the most parametric (most flexible for manipulation). Some examples are provided of using various synthesis techniques to sonify body position, desktop GUI interactions, stock data, etc. Reference: Cook, P. R. (2011). Sound synthesis for auditory display. In Hermann, T., Hunt, A., Neuhoff, J. G., editors, The Sonification Handbook, chapter 9, pages 197–235. Logos Publishing House, Berlin, Germany. Media examples: http://sonification.de/handbook/chapters/chapter9 18 Chapter 9 Sound Synthesis for Auditory Display Perry R. Cook 9.1 Introduction and Chapter Overview Applications and research in auditory display require sound synthesis and manipulation algorithms that afford careful control over the sonic results. The long legacy of research in speech, computer music, acoustics, and human audio perception has yielded a wide variety of sound analysis/processing/synthesis algorithms that the auditory display designer may use. This chapter surveys algorithms and techniques for digital sound synthesis as related to auditory display. -
Wavetable Synthesis 101, a Fundamental Perspective
Wavetable Synthesis 101, A Fundamental Perspective Robert Bristow-Johnson Wave Mechanics, Inc. 45 Kilburn St., Burlington VT 05401 USA [email protected] ABSTRACT: Wavetable synthesis is both simple and straightforward in implementation and sophisticated and subtle in optimization. For the case of quasi-periodic musical tones, wavetable synthesis can be as compact in data storage requirements and as general as additive synthesis but requires much less real-time computation. This paper shows this equivalence, explores some suboptimal methods of extracting wavetable data from a recorded tone, and proposes a perceptually relevant error metric and constraint when attempting to reduce the amount of stored wavetable data. 0 INTRODUCTION Wavetable music synthesis (not to be confused with common PCM sample buffer playback) is similar to simple digital sine wave generation [1] [2] but extended at least two ways. First, the waveform lookup table contains samples for not just a single period of a sine function but for a single period of a more general waveshape. Second, a mechanism exists for dynamically changing the waveshape as the musical note evolves, thus generating a quasi-periodic function in time. This mechanism can take on a few different forms, probably the simplest being linear crossfading from one wavetable to the next sequentially. More sophisticated methods are proposed by a few authors (recently Horner, et al. [3] [4]) such as mixing a set of well chosen basis wavetables each with their corresponding envelope function as in Fig. 1. The simple linear crossfading method can be thought of as a subclass of the more general basis mixing method where the envelopes are overlapping triangular pulse functions. -
Tektronix Signal Generator
Signal Generator Fundamentals Signal Generator Fundamentals Table of Contents The Complete Measurement System · · · · · · · · · · · · · · · 5 Complex Waves · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 15 The Signal Generator · · · · · · · · · · · · · · · · · · · · · · · · · · · · 6 Signal Modulation · · · · · · · · · · · · · · · · · · · · · · · · · · · 15 Analog or Digital? · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 7 Analog Modulation · · · · · · · · · · · · · · · · · · · · · · · · · 15 Basic Signal Generator Applications· · · · · · · · · · · · · · · · 8 Digital Modulation · · · · · · · · · · · · · · · · · · · · · · · · · · 15 Verification · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 8 Frequency Sweep · · · · · · · · · · · · · · · · · · · · · · · · · · · 16 Testing Digital Modulator Transmitters and Receivers · · 8 Quadrature Modulation · · · · · · · · · · · · · · · · · · · · · 16 Characterization · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 8 Digital Patterns and Formats · · · · · · · · · · · · · · · · · · · 16 Testing D/A and A/D Converters · · · · · · · · · · · · · · · · · 8 Bit Streams · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 17 Stress/Margin Testing · · · · · · · · · · · · · · · · · · · · · · · · · · · 9 Types of Signal Generators · · · · · · · · · · · · · · · · · · · · · · 17 Stressing Communication Receivers · · · · · · · · · · · · · · 9 Analog and Mixed Signal Generators · · · · · · · · · · · · · · 18 Signal Generation Techniques -
Wavetable FM Synthesizer [RACK EXTENSION] MANUAL
WTFM Wavetable FM Synthesizer [RACK EXTENSION] MANUAL 2021 by Turn2on Software WTFM is not an FM synthesizer in the traditional sense. Traditional Wavetable (WT) synthesis. 4 oscillators, Rather it is a hybrid synthesizer which uses the each including 450+ Wavetables sorted into flexibility of Wavetables in combination with FM categories. synthesizer Operators. Classical 4-OP FM synthesis: each operator use 450+ WTFM Wavetable FM Synthesizer produces complex Wavetables to modulate other operators in various harmonics by modulating the various selectable WT routing variations of 24 FM Algorithms. waveforms of the oscillators using further oscillators FM WT Mod Synthesis: The selected Wavetable (operators). modulates the frequency of the FM Operators (Tune / Imagine the flexibility of the FM Operators using this Ratio). method. Wavetables are a powerful way to make FM RINGMOD Synthesis: The selected Wavetable synthesis much more interesting. modulates the Levels of the FM Operators similarly to a RingMod WTFM is based on the classical Amp, Pitch and Filter FILTER FM Synthesis: The selected Wavetable Envelopes with AHDSR settings. PRE and POST filters modulates the Filter Frequency of the synthesizer. include classical HP/BP/LP modes. 6 FXs (Vocoder / EQ Band / Chorus / Delay / Reverb) plus a Limiter which This is a modern FM synthesizer with easy to program adds total control for the signal and colours of the traditional AHDSR envelopes, four LFO lines, powerful Wavetable FM synthesis. modulations, internal effects, 24 FM algorithms. Based on the internal wavetable's library with rich waveform Operators Include 450+ Wavetables (each 64 content: 32 categories, 450+ wavetables (each with 64 singlecycle waveforms) all sorted into individual single-cycle waveforms), up to 30,000 waveforms in all. -
Oscilators Simplified
SIMPLIFIED WITH 61 PROJECTS DELTON T. HORN SIMPLIFIED WITH 61 PROJECTS DELTON T. HORN TAB BOOKS Inc. Blue Ridge Summit. PA 172 14 FIRST EDITION FIRST PRINTING Copyright O 1987 by TAB BOOKS Inc. Printed in the United States of America Reproduction or publication of the content in any manner, without express permission of the publisher, is prohibited. No liability is assumed with respect to the use of the information herein. Library of Cangress Cataloging in Publication Data Horn, Delton T. Oscillators simplified, wtth 61 projects. Includes index. 1. Oscillators, Electric. 2, Electronic circuits. I. Title. TK7872.07H67 1987 621.381 5'33 87-13882 ISBN 0-8306-03751 ISBN 0-830628754 (pbk.) Questions regarding the content of this book should be addressed to: Reader Inquiry Branch Editorial Department TAB BOOKS Inc. P.O. Box 40 Blue Ridge Summit, PA 17214 Contents Introduction vii List of Projects viii 1 Oscillators and Signal Generators 1 What Is an Oscillator? - Waveforms - Signal Generators - Relaxatton Oscillators-Feedback Oscillators-Resonance- Applications--Test Equipment 2 Sine Wave Oscillators 32 LC Parallel Resonant Tanks-The Hartfey Oscillator-The Coipltts Oscillator-The Armstrong Oscillator-The TITO Oscillator-The Crystal Oscillator 3 Other Transistor-Based Signal Generators 62 Triangle Wave Generators-Rectangle Wave Generators- Sawtooth Wave Generators-Unusual Waveform Generators 4 UJTS 81 How a UJT Works-The Basic UJT Relaxation Oscillator-Typical Design Exampl&wtooth Wave Generators-Unusual Wave- form Generator 5 Op Amp Circuits -
Fourier Transforms
Fourier Transforms Mark Handley Fourier Series Any periodic function can be expressed as the sum of a series of sines and cosines (or varying amplitides) 1 Square Wave Frequencies: f Frequencies: f + 3f Frequencies: f + 3f + 5f Frequencies: f + 3f + 5f + … + 15f Sawtooth Wave Frequencies: f Frequencies: f + 2f Frequencies: f + 2f + 3f Frequencies: f + 2f + 3f + … + 8f 2 Fourier Series A function f(x) can be expressed as a series of sines and cosines: where: Fourier Transform Fourier Series can be generalized to complex numbers, and further generalized to derive the Fourier Transform. Forward Fourier Transform: Inverse Fourier Transform: Note: 3 Fourier Transform Fourier Transform maps a time series (eg audio samples) into the series of frequencies (their amplitudes and phases) that composed the time series. Inverse Fourier Transform maps the series of frequencies (their amplitudes and phases) back into the corresponding time series. The two functions are inverses of each other. Discrete Fourier Transform If we wish to find the frequency spectrum of a function that we have sampled, the continuous Fourier Transform is not so useful. We need a discrete version: Discrete Fourier Transform 4 Discrete Fourier Transform Forward DFT: The complex numbers f0 … fN are transformed into complex numbers F0 … Fn Inverse DFT: The complex numbers F0 … Fn are transformed into complex numbers f0 … fN DFT Example Interpreting a DFT can be slightly difficult, because the DFT of real data includes complex numbers. Basically: The magnitude of the complex number for a DFT component is the power at that frequency. The phase θ of the waveform can be determined from the relative values of the real and imaginary coefficents. -
Tooth Wave Supplied to One Deflection Axis of 50 Field of Search
United States Patent (11) 3,633,066 72) Inventors Kozo Uchida; Naohisa Nakaya; Koji Suzuki, all of Tokyo, 56 References Cited Japan UNITED STATES PATENTS (21) Appl. No. 851,609 3,432,762 3/1969 La Porta....................... 328/179 22) Fied Aug. 20, 1969 3,571,617 3/1971 Hainz........................... 307/228 45) Patented Jan. 4, 1972 Primary Examiner-Rodney D. Bennett, Jr. 73 Assignee Iwatsu Electric Company Limited Assistant Examiner-H. A. Birmiel Tokyo, Japan Attorney-Chittick, Pfund, Birch, Samuels & Gauthier 32) Priority Aug. 23, 1968 33 Japan 31) 43/59922 ABSTRACT: In a sampling device including a synchronizing device comprising a synchronizing circuit, a sampler, an oscil loscope, and a synchronism control circuit having a dif 54) AUTOMATICSYNCHRONIZING SYSTEMSFOR ferentiation circuit to differentiate the output from the sam SAMPLNG EDEVICES pler to vary a variable element in the synchronizing circuit whereby to stop variation of the variable element and to main 3 Claims, 7 Drawing Figs. tain the same in the stopped condition upon reaching 52) U.S.C........................................................ 315/19, synchronism there is provided means to stop the operation of 307/228, 315125,328/72,328/179 the synchronism control circuit over the flyback interval of a (51) Int. Cl......................................................... H01j29/70 low-speed sawtooth wave supplied to one deflection axis of 50 Field of Search............................................ 307/228; the oscilloscope to prevent loss of synchronization which 328/63, 72, 179, 151; 315/18, 19, 22, 25 otherwise tends to occur during the flyback interval. LOW SP SAW 48SAMPLNGPULSE GEN COMPARATOR TOOTH WAVE GEN SYNCHRONIZING HGH SP SAW CKT TOOTH WAVE GEN 46 PATENTEDIAN 4972 3,633,066 SHEET 1 OF 2 - - - - - - - - - - was - - - - - - - - - - - - - -- a-- - - - F. -
Experiment 4: Time-Varying Circuits
Name/NetID: Teammate/NetID: Experiment 4: Time-Varying Circuits Laboratory Outline: Last week, we analyzed simple circuits with constant voltages using the DC power supply and digital multimeter (DMM). This week, we’ll learn to deal with voltages that vary over time by using the function generator and oscilloscope which can be found on your lab bench. Once this lab is complete, you’ll understand how and when to use all the bench equipment in the ECE 110 Lab. Unless an experiment requires a particularly-obscure capability from these devices, all future procedures will assume you understand how to take the necessary measurements using the necessary sources and meters. In addition, you will have expanded your knowledge on constructing prototype circuits and will be able to build most circuits required of future experiments. Using the Oscilloscope and Function Generator: In order to analyze voltages that vary with time, we must use a measurement device that can capture a time history of those voltages. This device is called an oscilloscope. In addition, there are many situations in which we might desire to generate a specific periodic voltage without having to build a special circuit to do so. We can do this using what is called a function generator (sometimes called a signal generator or waveform generator). Once we have mastered the use of these pieces of bench equipment, we’ll have all the basic skills needed for the rest of the semester. Notes: Function Generator Important! The function A function generator is a piece of equipment that outputs an electrical waveform that can vary in time, in contrast to the DC generator operates like an ideal power supply that can only output a constant voltage. -
Delta Modulation
DELTA MODULATION PREPARATION ...............................................................................122 principle of operation...............................................................122 block diagram.........................................................................................122 step size calculation................................................................................124 slope overload and granularity.................................................124 slope overload ........................................................................................124 granular noise.........................................................................................125 noise and distortion minimization ..........................................................126 EXPERIMENT .................................................................................126 setting up..................................................................................126 slope overload..........................................................................129 the ADAPTIVE CONTROL signal................................................................129 the output .................................................................................130 complex message.....................................................................131 TUTORIAL QUESTIONS................................................................132 APPENDIX.......................................................................................133 a ‘complex’