Knowledge (XXG)

Real computation

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20: 411: 105:'s idealized analog computer can only solve algebraic differential equations, while a digital computer can solve some transcendental equations as well. However this comparison is not entirely fair since in 330: 293: 109:'s idealized analog computer computations are immediately done; i.e. computation is done in real time. Shannon's model can be adapted to cope with this problem.) 93:
is concerned). Depending on the model chosen, this may enable real computers to solve problems that are inextricable on digital computers (For example,
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can have noncomputable real weights, making them able to compute nonrecursive languages.) or vice versa. (
193:"Polynomial differential equations compute all real computable functions on computable compact intervals" 481: 132: 43: 58:. Within this theory, it is possible to prove interesting statements such as "The complement of the 19: 368: 324: 287: 74: 364: 346: 273: 422: 418: 385: 214: 204: 148: 136: 70: 34:
a given function. Real computation theory investigates properties of such devices under the
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Computational complexity of real valued recursive functions and analog circuits
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The "Liquid Computer" A Novel Strategy for Real-Time Computing on Time Series
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If real computation were physically realizable, one could use it to solve
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O. Bournez; M. L. Campagnolo; D. S. Graça & E. Hainry (Jun 2007).
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models (digital computers, in this context, should be thought of as
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deals with hypothetical computing machines using infinite-precision
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These hypothetical computing machines can be viewed as idealised
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Neural Networks and Analog Computation: Beyond the Turing Limit
54:. They are given this name because they operate on the set of 305:. Universidade TĂ©cnica de Lisboa, Instituto Superior TĂ©cnico. 426: 157:, for a generalization to arbitrary geometrical spaces. 310:
Natschläger, Thomas, Wolfgang Maass, Henry Markram.
112:A canonical model of computation over the reals is 246:News, Vol. 36, No. 1. (March 2005), pp. 30–52. 446: 8: 329:: CS1 maint: multiple names: authors list ( 292:: CS1 maint: multiple names: authors list ( 177:A Simple Introduction to Computable Analysis 369:"On the computational power of neural nets" 453: 439: 301:Campagnolo, Manuel Lameiras (July 2001). 239:NP-complete Problems and Physical Reality 218: 208: 89:, at least insofar as their operation on 377:Journal of Computer and System Sciences 166: 69:which operate on real numbers, whereas 322: 285: 77:. They may be further subdivided into 7: 407: 405: 262:, Felipe Cucker, Michael Shub, and 151:, for other such powerful machines. 425:. You can help Knowledge (XXG) by 14: 38:assumption of infinite precision. 409: 269:Complexity and Real Computation 16:Concept in computability theory 62:is only partially decidable." 1: 503: 404: 210:10.1016/j.jco.2006.12.005 174:Klaus Weihrauch (1995). 155:Quantum finite automaton 127:-complete problems, in 114:Blum–Shub–Smale machine 487:Computer science stubs 390:10.1006/jcss.1995.1013 39: 472:Models of computation 197:Journal of Complexity 133:holographic principle 22: 44:computability theory 361:Siegelmann, Hava T. 123:problems, and even 365:Sontag, Eduardo D. 75:computable numbers 40: 434: 433: 341:(December 1998). 71:digital computers 494: 477:Hypercomputation 455: 448: 441: 419:computer science 413: 406: 401: 373: 356: 339:Siegelmann, Hava 334: 328: 320: 318: 306: 297: 291: 283: 247: 231: 225: 224: 222: 212: 188: 182: 181: 171: 149:Hypercomputation 137:Bekenstein bound 91:computable reals 67:analog computers 48:real computation 46:, the theory of 28:analog computing 502: 501: 497: 496: 495: 493: 492: 491: 462: 461: 460: 459: 371: 359: 353: 337: 321: 316: 309: 300: 284: 280: 258: 255: 253:Further reading 250: 232: 228: 190: 189: 185: 173: 172: 168: 164: 145: 129:polynomial time 95:Hava Siegelmann 73:are limited to 24:Circuit diagram 17: 12: 11: 5: 500: 498: 490: 489: 484: 479: 474: 464: 463: 458: 457: 450: 443: 435: 432: 431: 414: 403: 402: 384:(1): 132–150. 357: 351: 335: 307: 298: 278: 254: 251: 249: 248: 234:Scott Aaronson 226: 203:(3): 317–335. 183: 165: 163: 160: 159: 158: 152: 144: 141: 107:Claude Shannon 103:Claude Shannon 60:Mandelbrot set 15: 13: 10: 9: 6: 4: 3: 2: 499: 488: 485: 483: 480: 478: 475: 473: 470: 469: 467: 456: 451: 449: 444: 442: 437: 436: 430: 428: 424: 421:article is a 420: 415: 412: 408: 399: 395: 391: 387: 383: 379: 378: 370: 366: 362: 358: 354: 352:0-8176-3949-7 348: 344: 340: 336: 332: 326: 315: 314: 308: 304: 299: 295: 289: 281: 279:0-387-98281-7 275: 271: 270: 265: 264:Stephen Smale 261: 257: 256: 252: 245: 241: 240: 235: 230: 227: 221: 216: 211: 206: 202: 198: 194: 187: 184: 179: 178: 170: 167: 161: 156: 153: 150: 147: 146: 142: 140: 138: 134: 130: 126: 122: 117: 115: 110: 108: 104: 100: 96: 92: 88: 84: 80: 76: 72: 68: 63: 61: 57: 53: 49: 45: 37: 33: 29: 25: 21: 482:Real numbers 427:expanding it 416: 381: 375: 342: 312: 302: 268: 237: 229: 220:10400.1/1011 200: 196: 186: 176: 169: 118: 111: 79:differential 64: 56:real numbers 52:real numbers 47: 41: 260:Lenore Blum 121:NP-complete 99:neural nets 87:topological 30:element to 466:Categories 162:References 36:idealizing 325:cite book 288:cite book 83:algebraic 32:integrate 367:(1995). 266:(1998). 143:See also 135:and the 398:1322637 116:(BSS). 396:  349:  276:  244:SIGACT 242:, ACM 26:of an 417:This 372:(PDF) 317:(PDF) 423:stub 347:ISBN 331:link 294:link 274:ISBN 81:and 386:doi 215:hdl 205:doi 97:'s 42:In 468:: 394:MR 392:. 382:50 380:. 374:. 363:; 345:. 327:}} 323:{{ 290:}} 286:{{ 272:. 236:, 213:. 201:23 199:. 195:. 139:. 125:#P 454:e 447:t 440:v 429:. 400:. 388:: 355:. 333:) 319:. 296:) 282:. 223:. 217:: 207:: 180:.

Index


Circuit diagram
analog computing
integrate
idealizing
computability theory
real numbers
real numbers
Mandelbrot set
analog computers
digital computers
computable numbers
differential
algebraic
topological
computable reals
Hava Siegelmann
neural nets
Claude Shannon
Claude Shannon
Blum–Shub–Smale machine
NP-complete
#P
polynomial time
holographic principle
Bekenstein bound
Hypercomputation
Quantum finite automaton
A Simple Introduction to Computable Analysis
"Polynomial differential equations compute all real computable functions on computable compact intervals"

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