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Sample Number Harm. No. o 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Spectrum C 0 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 _ C 8 1.000 -1.000 1.000 -1.000 1.000 -1.000 -1.000 -1.000 1.000 -1.000 1.000 -1.000 1.000 - 1.000 1.000 -1.000 _ C 1 1.000 .924 .707 .383 .000 - .383 - .707 - .924 -1.000 - .924 - .707 - .383 ,000 .383 .707 .924 _ S 1 .000 .383 .707 .924 1.000 .924 .707 .383 .000 .383 .707 .924 -1.000 .924 .707 ,383 _ C2 1.000 .707 .000 - .707 -1.000 .707 .000 .707 1.000 .707 .000 .707 -1.000 ,707 .000 .707 _ S2 .000 .707 1.000 .707 .000 .707 -1.000 .707 .000 .707 1.000 ,707 .000 -,707 -1.000 -.707 _ C3 1.000 .383 - .707 - .924 .000 .924 .707 - .383 - 1.000 - .383 .707 .924 .000 - .924 - ,707 .383 _ S3 .000 .924 .707 - .383 -1.000 - .383 .707 .924 .000 - .924 - .707 .383 1.000 .383 - ,707 - .924 _ C4 1.000 .000 -1.000 .000 1.000 .000 -1.000 .000 1.000 .000 -1.000 .000 1.000 .000 -1.000 .000 _ S4 .000 1.000 .000 -1.000 .000 1.000 .000 -1.000 .000 1.000 .000 -1.000 ,000 1.000 ,000 -1,000 _ C5 1.000 - .383 - .707 .924 .000 -.924 .707 .383 -1.000 ,383 .707 -.924 .000 .924 -.707 -,383 _ S5 .000 .924 -.707 - .383 1.000 .383 -.707 .924 ,000 - ,924 .707 .383 -1.000 .383 ,707 -.924 _ C6 1.000 - .707 .000 .707 -1.000 .707 .000 -.707 1.000 -.707 .000 .707 -1.000 ,707 .000 -.707 _ S6 .000 .707 -1.000 .707 .000 - .707 1.000 - ,707 .000 .707 -1.000 .707 .000 -.707 1.000 -.707 _ C7 1.000 -.924 .707 -.383 .000 .383 - .707 .924 -1.000 .924 - ,707 .383 .000 -.383 ,707 -.924 _ S7 .000 .383 -.707 .924 1.000 .924 - .707 .383 .000 - ,383 .707 - ,924 1.000 - .924 ,707 - .383 _ Fig. 13-11. (A) Slow Fourier transform worksheet. ti Q ~I""' 2 z tTl ~ ZtTl ?" ~ ~ >-l tTl () ::r: zZc:: tTl (fJ *" VJ *"
Sample Spectrum' ~ Number 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 ~ ~ Harm. No. .310 .694 .473 .515 .339 .334 .171 .142 -.013 -.060 -.209 -.277 -.419 -.517 -.652 -.830 C 0 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 .000 .310 .694 .473 .515 .339 .334 .171 .142 -.013 -.060 -.209 -.277 -.419 -.517 -.652 -.830 C8 1.000 -1.000 1.000 -1.000 1.000 -1.000 1.000 -1.000 1.000 -1.000 1.000 -1.000 1.000 -1.000 1.000 -1.000 .000 C 1 .310 1.000 .310 -.694 .473 -.515 .339 -.334 .171 -.142 -.013 .060 -.209 .277 -.419 .517 -.652 .830 .924 .707 .383 .000 .383 -.707 -.924 -1.000 -.924 -.707 -.383 $:: .000 .383 .707 .924 .000 .641 e .334 .197 .000 -.128 -.121 -.131 .013 .055 .148 .106 .000 .198 .461 .767 CFJ S 1 .000 .383 .707 .924 1.000 .924 .707 .383 .000 -.383 -.707 -.924 -1.000 -.924 -.707 -.383 .500 () .000 .266 .334 .476 .339 .309 .121 .054 .000 .023 .148 .256 .419 .478 .461 .318 > t""' C 2 1.000 .707 .000 -.707 -1.000 -.707 .000 .707 1.000 .707 .000 -.707 -1.000 -.707 .000 .707 037 .310 .491 .000 -.364 -.339 -.236 .000 .100 -.013 -.042 .000 .196 .419 .366 .000 -.587 "1i S 2 .000 .707 1.000 .707 .000 -.707 -1.000 -.707 .000 .707 1.000 .707 .000 -.707 -1.000 -.707 .247 "1i t""' .000 .491 .473 .364 .000 -.236 -.171 -.100 .000 -.042 -.209 -.196 .000 .366 .652 .587 () C 3 1.000 .383 -.707 -.924 .000 .924 .707 - .383 -1.000 -.383 .707 .924 .000 -.924 -.707 .383 .049 .310 .266 -.334 -.476 .000 .309 .121 -.054 .013 .023 -.148 -.256 .000 .478 .461 -.318 ~ ... S 3 .000 .924 .707 -.383 -1.000 -.383 .707 .924 .000 -.924 -.707 .383 1.000 .383 -.707 -.924- .159 0 .000 .641 .334 -.197 -.339 -.128 .121 .131 .000 .055 .148 -.106 -.419 -.198 .461 .767 Z CFJ C 4 1.000 .000 -1.000 .000 1.000 .000 -1.000 .000 1.000 .000 -1.000 .000 1.000 .000 -1.000 .000 .054 .310 .000 -.473 .000 .339 .000 -.171 .000 -.013 .000 .209 .000 -.419 .000 .652 .000 0 >n S 4 .000 1.000 .000 -1.000 .000 1.000 .000 -1.000 .000 1.000 .000 -1.000 .000 1.000 .000 -1.000 .113 .000 .694 .000 -.515 .000 .334 .000 -.142 .000 -.060 .000 .277 .000 -.517 .000 .830 ... $:: C 5 1.000 -.383 -.707 .924 .000 -.924 .707 .383 -1.000 .383 .707 -.924 .000 .924 -.707 -.383 () .056 .310 -.266 -.334 .476 .000 -.309 .121 .054 .013 -.023 -.148 .256 .000 -.478 .461 .318 ~ S 5 .000 .924 -.707 -.383 1.000 -.383 -.707 .924 .000 -.924 .707 .383 -1.000 .383 .707 .924 .083 "1i .000 .641 -.334 -.197 .339 -.128 -.121 .131 .000 .055 -.148 -.106 .419 -.198 -.461 .767 ~ C 6 1.000 -.707 .000 .707 -1.000 .707 .000 -.707 1.000 -.707 .000 .707 -1.000 .707 .000 -.707 .057 () .310 -.491 .000 .364 -.339 .236 tti .000 -.100 -.013 .042 .000 -.196 .419 -.366 .000 .587 CFJ CFJ S 6 .000 .707 1.000 .707 .000 -.707 1.000 -.707 .000 .707 -1.000 .707 .000 -.707 1.000 -.707 .061 0 .000 .491 -.473 .364 .000 -.236 .171 -.100 .000 -.042 .209 -.196 .000 .366 -.652 .587 ?' CFJ C 7 1.000 -.924 .707 -.383 .000 .383 -.707 .924 -1.000 .924 -.707 .383 .000 -.383 .707 -.924 .056 .310 -.641 .334 -.197 .000 .128 -.121 .131 -.013 -.055 .148 -.106 .000 .198 -.461 .767 S 7 .000 .383 -.707 .924 -1.000 .924 -.707 .383 .000 -.383 .707 -.924 1.000 -.924 .707 -.383 .044 .000 .266 -.334 .476 -.339 .309 -.121 .054 .000 .023 -.148 .256 -.419 .478 -.461 .318 Note 1: Entries are the true sum divided by 8 >- Fig. 13-11. (Cant.). (B) Worksheet filled in for forward Fourier transform.
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Musical Applications of Microproces
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© 19B5 by Hayden Books A Division
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serve to acquaint the general reade
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SECfrON II. Computer-Controlled Ana
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17. Digital Hardware 589 AnalogModu
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1 Music Synthesis Principles Creati
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MUSIC SYNTHESIS PRINCIPLES 5 own ar
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MusIC SYNTHESIS PRINCIPLES 7 Increa
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MUSIC SYNTHESIS PRINGPLES 9 VERY SM
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MUSIC SYNTHESIS PRINOPLES 11 repres
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MUSIC SYNTHESIS PRINCIPLES 13 The w
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MUSIC SYNTHESIS PRlNCIPLES 15 was c
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MUSIC SYNTHESIS PRlNOPlES 17 In act
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MUSIC SYNTHESIS PRINCIPLES 19 SIN (
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MUSIC SYNTHESIS PRINCIPLES 21 lILt!
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MUSIC SYNTHESIS PRINCIPLES 23 - ,--
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MUSIC SYNTHESIS PRINOPLES 25 + or--
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MUSIC SYNTHESIS PRINCIPLES 27 Human
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MUSIC SYNTHESIS PRINOPLES 29 fundam
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MUSIC SYNTHESIS PRINCIPLES 31 frequ
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MUSIC SYNTHESIS PRINCIPLES 33 from
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MUSIC SYNTHESIS PRINCIPLES 35 ever,
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MUSIC SYNTHESIS PRINCIPLES 37 have
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MUSIC SYNTHESIS PRINCIPLES 39 No li
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MUSIC SYNTHESIS PRINCIPLES 41 cropr
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44 MUSICAL ApPLICATIONS OF MICROPRO
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60 MUSICAL ApPLICATrONS OF MICROPRO
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68 MUSICAL ApPLICAnONS OF MICROPROC
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82 MUSICAL ApPUCATIONS OF MICROPROC
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84 MUSICAL ApPUCATIONS OF MICROPROC
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vvv·(B) 86 MUSICAL ApPLICATIONS OF
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100 MUSICAL ApPLICAnONS OF MICROPRO
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102 MUSICAL ApPLICATIONS OF MICROPR
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Table 5-1. 6502 Instruction Set Lis
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Coding Table 5-3. 68000 Addressing
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Table 5-4. 68000 Instruction Set Su
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Table 5-4. 68000 Instruction Set Su
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6 BasicAnalogModules Probably the m
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BASIC ANALOG MODULES 179 tage remai
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BASIC ANALOG MODULES 181 Op-amps ma
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BASIC ANALOG MODULES 183 '0: :? u
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BASIC ANALOG MODULES 185 with an id
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BASIC ANALOG MODULES 187 EXPONENTIA
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BASIC ANALOG MODULES 189 (or 0.9766
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BASIC ANALOG MODULES 191 4R Vr'o'M
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BASIC ANALOG MODULES 193 tooth with
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BASIC ANALOG MODULES 195 +IOVrel PU
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BASIC ANALOG MODULES 197 Table 6-1.
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BASIC ANALOG MODULES 199 constants
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BASIC ANALOG MODULES 201 12 ~ E 1-
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BASIC ANALOG MODULES 203 R2 R3 100
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BASIC ANALOG MODULES 205 fore, must
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BASIC ANALOG MODULES 207 For peak p
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BASIC ANALOG MODULES 209 22 pF RI S
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BASIC ANALOG MODULES 211 INPUT~OUTP
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BASIC ANALOG MODULES 213 Voltage-Tu
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BASIC ANALOG MODULES 215 +20 +15 +1
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BASIC ANALOG MODULES 217 100 ko. BA
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BASIC ANALOG MODULES 219 +15 V0----
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Digital-to-Analog and tlnalog-to-Di
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DIGITAL-TO-ANALOG AND ANALOG-TO-DIG
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300 MUSICAl ApPLICATIONS OF MICROPR
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11 CORtrolSequeRce Display andEditi
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CONTROL SEQUENCE DISPLAY AND EDITIN
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SECTIONIII DigitalSynthesis antl So
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Page 405 and 406: 392 MUSICAL ApPLICATIONS OF MICROPR
Page 411 and 412: Table 12·1. Design Data for Chebys
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Page 430 and 431: 13 Digital Tone Generation Teehniqu
Page 432 and 433: DIGITAL TONE GENERATION TECHNIQUES
Page 458 and 459: Sample Spectrum Number 0 1 2 3 4 5
Page 482 and 483: 1,0 0,8 0,6 0.4 0,2 °0 10 12 14 16
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Page 494 and 495: 14 DigitalFiltering In analog synth
Page 496 and 497: DIGITAL FILTERING 483 Input Samples
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DIGITAL. FILTERING 493 circuits mak
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DIGITAL FILTERING 495 OUTPUT Fig. 1
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DIGITAL FILTERING 497 INPUT ~8~~~~~
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DIGITAL FILTERING 499 the turnover
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DIGITAL FILTERING 501 frequency is
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+ 3 1 oL-_-...l__---l__---L__---r-_
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DIGITAL FILTERING 505 When programm
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DIGITAL FILTERING 507 lowest freque
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DIGITAL FILTERING 509 Even with a p
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DIGITAL FILTERING 511 OUTPUT Fig. 1
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DIGITAL FILTERING 513 INPUT VARIABL
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DIGITAL FILTERING 515 INPUT (C) -(.
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DIGITAL FILTERING 517 NOTE: Xl, Y,
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DIGITAL FILTERING 519 AMPLITUDE, (d
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DIGITAL FILTERING 521 o ~ -10 ~ -20
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DIGITAL FILTERING 523 1.0 0.8 0.6
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DIGITAL FILTERING 525 When the outp
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16 Source-SignalAnalys,is One of th
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SOURCE-SIGNAL ANALYSIS 545 nOdB T I
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--------, I I ! II i I I I I , , i"
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SOURCE-SIGNAL ANALYSIS 549 3 IN -"
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SOURCE-SIGNAL ANALYSIS 551 Data Rep
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SOURCE-SIGNAL ANALYSIS 553 SIGNAL B
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SOURCE-SIGNAL ANALYSIS 555 -5° FH
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SOURCE-SIGNAL ANALYSIS 557 -5 -10 ~
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SOURCE-SIGNAL ANALYSIS 559 Since th
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SOURCE-SIGNAL ANALYSIS 561 o -5 -10
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SOURCE-SIGNAL ANALYSIS 563 o -5 -10
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SOURCE-SIGNAL ANALYSIS 565 overlapp
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SOURCE-SIGNAL ANALYSIS 567 • ....
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SOURCE-SIGNAL ANALYSIS 569 from an
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SOURCE-SIGNAL ANALYSIS 571 componen
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SOURCE-SIGNAL ANALYSIS 573 and some
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SOURCE-SIGNAL ANALYSIS 575 185491 A
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SOURCE-SIGNAL ANALYSIS 577 SYSTEM F
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SOURCE-SIGNAL ANALYSIS 579 (AI (BI
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SOURCE-SIGNAL ANALYSIS 581 (Gl II'
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SOURCE-SIGNAL ANALYSIS 583 PULSE PE
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SOURCE-SIGNAL ANALYSIS 585 again, t
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SOURCE-SIGNAL ANALYSIS 587 Quite ob
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17 DigitalHardware At this point, w
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DIGITAL HARDWARE 591 Lsa I N+I DIVI
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DIGITAL HARDWARE 593 (~OCK[ L _ LSB
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DIGITAL HARDWARE 595 FREQUENCY CONT
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DIGITAL HARDWARE 597 Fig. 17-7. Pha
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DIGITAL HARDWARE 599 MOST SIGNIFICA
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DIGITAL HARDWARE 601 waveform chang
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DIGITAL HARDWARE 603 As an example,
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DIGITAL HARDWARE 605 1. Sixteen ind
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DIGITAL HARDWARE 607 discussed, the
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DIGITAL HARDWARE 609 between the 41
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DIGITAL HARDWARE 611 8-BIT PORT I M
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FREOUENCY CONTROL IN I I 20 FREOUEN
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DIGITAL HARDWARE 615 TO MULTIPLEXED
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FREQ. :a.-8 CNTL. WRITE FREQ. I 20
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DIGITAL HARDWARE 619 effective freq
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DIGITAL HARDWARE 621 The signal mem
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DIGITAL HARDWARE 623 into a filter
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DIGITAL HARDWARE 625 made using con
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DIGITAL HARDWARE 627 A Hybrid Voice
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DIGITAL HARDWARE 629 o -5 -10 -15 ~
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DIGITAL HARDWARE 631 o -5 -10 -15 ~
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DIGITAL HARDWARE 633 D3 02 01 10 00
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DIGITAL HARDWARE 635 plementers on
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DIGITAL HARDWARE 637 taken care of
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SECTIONIV ProductApplications andth
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716 MUSICAL ApPLICATIONS OF MJCROPR
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RING MOD VCD A PITCHo--+lcNTL OUT A
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20 Low-CostSYllthesis Techniques Wh
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LOW-COST SYNTHESIS TECHNIQUES 759 g
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LOW-COST SYNTHESIS TECHNIQUES 761 i
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LOW-COST SYNTHESIS TECHNIQUES 763 0
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LOW-COST SYNTHESIS TECHNIQUES 765 S
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LOW-COST SYNTHESIS TECHNIQUES 767 c
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LOW-COST SYNTHESIS TECHNIQUES 769 O
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LOW-COST SYNTHESIS TECHNIQUES 771 +
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LOW-COST SYNTHESIS TECHNIQUES 773 F
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LOW-COST SYNTHESIS TECHNIQUES 775 F
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LOW-COST SYNTHESIS TECHNIQUES 777 f
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21 Future Frequently, when glvmg ta
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LOW-COST SYNTHESIS TECHNIQUES 781 T
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LOW-COST SYNTHESIS TECHNIQUES 783 t
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LOW-COST SYNTHESIS TECHNIQUES 785 "
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LOW-COST SYNTHESIS TECHNIQUES 787 m
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LOW-COST SYNTHESIS TECHNIQUES 789 a
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Bibliography The following publicat
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BIBLIOGRAPHY 793 DMA DOS FET FFT FI
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(Communication) Minor - Computer Sc
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newsletter, writing numerous articl
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conversion subsystem, especially if
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In the beginning the company was su
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HAL : I really haven't kept up with
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was clear he was serious, I named m
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influences too like interrupts from
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SONIK : What activities do you do o
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as a homework assignment. So much o
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Musical Applications of Microproces
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