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S transform

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frequency burst. On the other hand, as the STFT consists of a constant window width, it leads to the result having poorer definition. In the second experiment, two more high frequency bursts are added to crossed chirps. In the result, all four frequencies were detected by the S transform. On the other hand, the two high frequencies bursts are not detected by STFT. The high frequencies bursts cross term caused STFT to have a single frequency at lower frequency.
1649:, meanwhile, the window function for S-Transform is a function of f. With a window function proportional to frequency, S Transform performs well in frequency domain analysis when the input frequency is low. When the input frequency is high, S-Transform has a better clarity in the time domain. As table below. 74:
transform algorithm was invented in 2010. It reduces the computational complexity from O to O and makes the transform one-to-one, where the transform has the same number of points as the source signal or image, compared to storage complexity of N for the original formulation. An implementation is
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Rocco Ditommaso, Marco Mucciarelli, Felice C. Ponzo (2010). S-Transform based filter applied to the analysis of non-linear dynamic behaviour of soil and buildings. 14th European Conference on Earthquake Engineering. Proceedings Volume. Ohrid, Republic of Macedonia. August 30 – September 3, 2010.
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transform and short-time Fourier transform (STFT). First, a high frequency signal, a low frequency signal, and a high frequency burst signal are used in the experiment to compare the performance. The S transform characteristic of frequency dependent resolution allows the detection of the high
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Rocco Ditommaso, Felice Carlo Ponzo, Gianluca Auletta (2015). Damage detection on framed structures: modal curvature evaluation using Stockwell Transform under seismic excitation. Earthquake Engineering and Engineering Vibration. June 2015, Volume 14, Issue 2, pp
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The main problem with the Wigner Transform is the cross term, which stems from the auto-correlation function in the Wigner Transform function. This cross term may cause noise and distortions in signal analyses. S-transform analyses avoid this issue.
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Brown, Robert A.; Lauzon, M. Louis; Frayne, Richard (January 2010). "A General Description of Linear Time-Frequency Transforms and Formulation of a Fast, Invertible Transform That Samples the Continuous S-Transform Spectrum Nonredundantly".
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M. Mucciarelli, M. Bianca, R. Ditommaso, M.R. Gallipoli, A. Masi, C Milkereit, S. Parolai, M. Picozzi, M. Vona (2011). FAR FIELD DAMAGE ON RC BUILDINGS: THE CASE STUDY OF NAVELLI DURING THE L’AQUILA (ITALY) SEISMIC SEQUENCE, 2009.
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Jaya Bharata Reddy, Dusmanta Kumar Mohanta, and B. M. Karan, "Power system disturbance recognition using wavelet and s-transform techniques," Birla institute of Technology, Mesra, Ranchi-835215, 2004.
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Ray, Prakash K.; Mohanty, Soumya R.; Kishor, Nand; Dubey, Harish C. (2010). "Coherency determination in grid-connected distributed generation based hybrid system under islanding scenarios".
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and overcoming some of its disadvantages. For one, modulation sinusoids are fixed with respect to the time axis; this localizes the scalable Gaussian window dilations and translations in
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J. J. Ding, "Time-frequency analysis and wavelet transform course note," the Department of Electrical Engineering, National Taiwan University (NTU), Taipei, Taiwan, 2007.
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A general formulation of the S transform makes clear the relationship to other time frequency transforms such as the Fourier, short time Fourier, and wavelet transforms.
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B. Boashash, "Notes on the use of the wigner distribution for time frequency signal analysis", IEEE Trans. on Acoust. Speech. and Signal Processing, vol. 26, no. 9, 1987
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transform has been proven to be able to identify a few types of disturbances, like voltage sag, voltage swell, momentary interruption, and oscillatory transients.
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Hongmei Zhu, and J. Ross Mitchell, "The S Transform in Medical Imaging," University of Calgary Seaman Family MR Research Centre Foothills Medical Centre, Canada.
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F. Hlawatsch and G. F. Boudreuax-Bartels, 1992 "Linear and quadratic timefrequency signal representations", IEEE Signal Processing Magazine, pp. 21–67
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transform generates contours which are suitable for simple visual inspection. However, wavelet transform requires specific tools like standard
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This kind of property makes S-Transform a powerful tool to analyze sound because human is sensitive to low frequency part in a sound signal.
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The only difference between the Gabor transform (GT) and the S transform is the window size. For GT, the windows size is a Gaussian function
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E. Sejdić, I. Djurović, J. Jiang, "Time-frequency feature representation using energy concentration: An overview of recent advances,"
1433: 1188:{\displaystyle S_{x}(n\Delta _{T}\,,m\Delta _{F})=\sum _{p=0}^{N-1}X\,e^{-\pi {\frac {p^{2}}{m^{2}}}}\,e^{\frac {j2pn}{N}}} 846:{\displaystyle S_{x}(t,f)=\int _{-\infty }^{\infty }X(f+\alpha )\,e^{-\pi \alpha ^{2}/f^{2}}\,e^{j2\pi \alpha t}\,d\alpha } 2291: 1777: 60: 40: 36: 1251: 268:{\displaystyle S_{x}(t,f)=\int _{-\infty }^{\infty }x(\tau )|f|e^{-\pi (t-\tau )^{2}f^{2}}e^{-j2\pi f\tau }\,d\tau } 1712: 2296: 574: 439: 1737: 1594: 634: 499: 2211:
Goupillaud, P.; Grossmann, A.; Morlet, J. (1984). "Cycle-octave and related transforms in seismic analysis".
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transform also be applied for other types of disturbances such as notches, harmonics with sag and swells etc.
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transform is derived as the phase correction of the continuous wavelet transform with window being the
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as a time–frequency distribution was developed in 1994 for analyzing geophysics data. In this way, the
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Stockwell, RG; Mansinha, L; Lowe, RP (1996). "Localization of the complex spectrum: the S transform".
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R. N. Bracewell, The Fourier Transform and Its Applications, McGraw Hill Book Company, New York, 1978
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D. Gabor, "Theory of communication", J. Inst. Elect. Eng., vol. 93, no. 3, pp. 429–457, 1946
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2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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The above definition implies that the s-transform function can be express as the convolution of
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This article is about the time–frequency transform. For the mathematical use of this term, see
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Brown, RA; Frayne, R (2008). "A fast discrete S-transform for biomedical signal processing".
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R. K. Young, Wavelet Theory and its Applications, Kluwer Academic Publishers, Dordrecht,1993
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I. Daubechies, "The wavelet transform, time-frequency localization and signal analysis",
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From the spectrum form of S-transform, we can derive the discrete-time S-transform.
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transform doesn't have a cross-term problem and yields a better signal clarity than
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Ditommaso, Rocco; Mucciarelli, Marco; Ponzo, Felice Carlo (2012).
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transform has its own disadvantages: the clarity is worse than
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Cohen, L. (1989). "Time-frequency distributions—A review".
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Kelly Sansom, "Fast S Transform", University of Calgary,
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https://www.ucalgary.ca/news/utoday/may31-2011/computing
1535:{\displaystyle B=X\cdot e^{-\pi {\frac {p^{2}}{m^{2}}}}} 998:
The Discrete time S-transform can then be expressed as:
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2010 IEEE International Conference on Power and Energy
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There are several ways to represent the idea of the
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Comparison with other time–frequency analysis tools
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Vol. 2008. pp. 2586–9. 65:Cohen's class distribution function 2112:Bulletin of Earthquake Engineering 2021:Bulletin of Earthquake Engineering 1480: 1407: 1356: 1319: 1224: 1108: 1043: 1026: 977: 950: 923: 902: 881: 751: 746: 341: 336: 318: 313: 158: 153: 14: 2177:IEEE Trans. on Information Theory 1661:Good clarity in frequency domain 2237:"Wavelets and signal processing" 2235:Rioul, O.; Vetterli, M. (1991). 2189:Annual Review of Fluid Mechanics 1682:Comparison with Wigner transform 2244:IEEE Signal Processing Magazine 1669:Bad clarity in frequency domain 1587:Comparison with Gabor transform 1430:Step4.Multiply Step2 and Step3 2201:10.1146/annurev.fluid.24.1.395 1636: 1625: 1612: 1598: 1565: 1553: 1489: 1476: 1464: 1461: 1452: 1440: 1416: 1403: 1391: 1388: 1365: 1349: 1331:{\displaystyle f=m\Delta _{F}} 1233: 1217: 1117: 1103: 1091: 1088: 1052: 1019: 771: 759: 732: 720: 687: 650: 642: 638: 618: 590: 584: 578: 552: 515: 507: 503: 483: 455: 449: 443: 368: 356: 299: 293: 212: 199: 184: 176: 172: 166: 139: 127: 1: 2104:http://roccoditommaso.xoom.it 969:is the sampling interval and 2225:10.1016/0016-7142(84)90025-5 2179:, vol. 36, no. 5, Sept. 1990 1778:Short-time Fourier transform 1745:Geophysical signal analysis 1672:Good clarity in time domain 61:Wigner distribution function 41:continuous wavelet transform 37:short-time Fourier transform 989:{\displaystyle \Delta _{F}} 962:{\displaystyle \Delta _{T}} 2318: 2139:The Fast Fourier Transform 2077:10.1109/PECON.2010.5697562 1875:10.1109/IEMBS.2008.4649729 1713:Magnetic resonance imaging 1658:Bad clarity in time domain 996:is the sampling frequency. 15: 2120:10.1007/s10518-010-9201-y 2041:10.1007/s10518-012-9338-y 2000:Digital Signal Processing 858:Discrete-time S-transform 47:transform. Moreover, the 1944:10.1109/tsp.2009.2028972 1738:multiresolution analysis 2302:Time–frequency analysis 1851:Stockwell, RG (1999). 1643: 1572: 1536: 1423: 1372: 1332: 1296: 1241: 1189: 1084: 990: 963: 936: 847: 694: 625: 559: 490: 417: 269: 39:(STFT), extending the 1749:Reflection seismology 1644: 1573: 1537: 1424: 1373: 1333: 1297: 1242: 1190: 1058: 991: 964: 937: 848: 695: 626: 560: 491: 418: 270: 1595: 1547: 1434: 1382: 1343: 1306: 1252: 1211: 1006: 973: 946: 868: 707: 635: 575: 500: 440: 287: 114: 94:transform. In here, 2292:Integral transforms 2256:1991ISPM....8...14R 2102:(downloadable from 2033:2012BuEE...10..895D 1936:2010ITSP...58..281B 1810:1996ITSP...44..998S 1695:We can compare the 1240:{\displaystyle X\,} 755: 345: 322: 279:Inverse S-Transform 162: 77:open source license 2183:Farge, M. (1992). 2071:. pp. 85–88. 1639: 1568: 1532: 1419: 1368: 1328: 1292: 1237: 1185: 986: 959: 932: 843: 738: 690: 621: 555: 486: 413: 328: 305: 265: 145: 2086:978-1-4244-8947-3 1988:. 13 August 2018. 1884:978-1-4244-1814-5 1828:10.1109/78.492555 1773:Wavelet transform 1768:Laplace transform 1754:Global seismology 1709:Signal filterings 1676: 1675: 1571:{\displaystyle B} 1528: 1422:{\displaystyle X} 1371:{\displaystyle X} 1288: 1182: 1154: 569:Fourier transform 100:Gaussian function 18:Laplace transform 2309: 2297:Fourier analysis 2275: 2264:10.1109/79.91217 2241: 2228: 2204: 2172: 2162: 2160:10.1.1.1026.2853 2091: 2090: 2064: 2058: 2055: 2049: 2044: 2018: 2009: 2003: 1996: 1990: 1989: 1982: 1976: 1970: 1964: 1963: 1918: 1905: 1904: 1862: 1856: 1849: 1840: 1839: 1821: 1793: 1652: 1648: 1646: 1645: 1640: 1635: 1634: 1633: 1632: 1577: 1575: 1574: 1569: 1541: 1539: 1538: 1533: 1531: 1530: 1529: 1527: 1526: 1517: 1516: 1507: 1488: 1487: 1428: 1426: 1425: 1420: 1415: 1414: 1377: 1375: 1374: 1369: 1364: 1363: 1337: 1335: 1334: 1329: 1327: 1326: 1301: 1299: 1298: 1293: 1291: 1290: 1289: 1287: 1286: 1277: 1276: 1267: 1246: 1244: 1243: 1238: 1232: 1231: 1194: 1192: 1191: 1186: 1184: 1183: 1178: 1164: 1157: 1156: 1155: 1153: 1152: 1143: 1142: 1133: 1116: 1115: 1083: 1072: 1051: 1050: 1034: 1033: 1018: 1017: 995: 993: 992: 987: 985: 984: 968: 966: 965: 960: 958: 957: 941: 939: 938: 933: 931: 930: 910: 909: 889: 888: 852: 850: 849: 844: 835: 834: 812: 811: 810: 809: 800: 795: 794: 754: 749: 719: 718: 699: 697: 696: 691: 686: 685: 684: 683: 674: 673: 653: 645: 630: 628: 627: 622: 617: 616: 564: 562: 561: 556: 551: 550: 549: 548: 539: 538: 518: 510: 495: 493: 492: 487: 482: 481: 422: 420: 419: 414: 405: 404: 382: 378: 355: 354: 344: 339: 321: 316: 274: 272: 271: 266: 257: 256: 232: 231: 230: 229: 220: 219: 187: 179: 161: 156: 126: 125: 2317: 2316: 2312: 2311: 2310: 2308: 2307: 2306: 2282: 2281: 2239: 2234: 2210: 2182: 2169:10.1109/5.30749 2144: 2137:E. O. Brigham, 2094: 2087: 2066: 2065: 2061: 2056: 2052: 2016: 2011: 2010: 2006: 1997: 1993: 1984: 1983: 1979: 1971: 1967: 1920: 1919: 1908: 1885: 1864: 1863: 1859: 1850: 1843: 1819:10.1.1.462.1500 1804:(4): 998–1001. 1795: 1794: 1790: 1786: 1764: 1706: 1693: 1684: 1624: 1601: 1593: 1592: 1589: 1584: 1579: 1545: 1544: 1542: 1518: 1508: 1495: 1479: 1432: 1431: 1429: 1406: 1380: 1379: 1355: 1341: 1340: 1338: 1318: 1304: 1303: 1278: 1268: 1255: 1250: 1249: 1247: 1223: 1209: 1208: 1204: 1201: 1165: 1159: 1144: 1134: 1121: 1107: 1042: 1025: 1009: 1004: 1003: 999: 997: 976: 971: 970: 949: 944: 943: 922: 901: 880: 866: 865: 863: 814: 801: 786: 775: 710: 705: 704: 675: 665: 654: 633: 632: 593: 573: 572: 566: 540: 530: 519: 498: 497: 458: 438: 437: 429: 384: 346: 327: 323: 285: 284: 233: 221: 211: 188: 117: 112: 111: 88: 55:. However, the 53:Gabor transform 21: 12: 11: 5: 2315: 2313: 2305: 2304: 2299: 2294: 2284: 2283: 2280: 2279: 2276: 2232: 2229: 2213:Geoexploration 2208: 2205: 2180: 2173: 2153:(7): 941–981. 2142: 2135: 2132: 2129: 2126: 2123: 2107: 2099: 2093: 2092: 2085: 2059: 2050: 2027:(3): 895–911. 2004: 1991: 1977: 1965: 1930:(1): 281–290. 1906: 1883: 1857: 1841: 1787: 1785: 1782: 1781: 1780: 1775: 1770: 1763: 1760: 1759: 1758: 1757: 1756: 1751: 1743: 1742: 1741: 1731: 1725: 1716: 1710: 1705: 1702: 1692: 1689: 1683: 1680: 1674: 1673: 1670: 1667: 1666:High-frequency 1663: 1662: 1659: 1656: 1638: 1631: 1627: 1623: 1620: 1617: 1614: 1611: 1608: 1604: 1600: 1588: 1585: 1583: 1580: 1578:). Repeat.} 1567: 1564: 1561: 1558: 1555: 1552: 1525: 1521: 1515: 1511: 1505: 1502: 1498: 1494: 1491: 1486: 1482: 1478: 1475: 1472: 1469: 1466: 1463: 1460: 1457: 1454: 1451: 1448: 1445: 1442: 1439: 1418: 1413: 1409: 1405: 1402: 1399: 1396: 1393: 1390: 1387: 1367: 1362: 1358: 1354: 1351: 1348: 1325: 1321: 1317: 1314: 1311: 1285: 1281: 1275: 1271: 1265: 1262: 1258: 1235: 1230: 1226: 1222: 1219: 1216: 1207:Step1.Compute 1206: 1200: 1197: 1196: 1195: 1181: 1177: 1174: 1171: 1168: 1162: 1151: 1147: 1141: 1137: 1131: 1128: 1124: 1119: 1114: 1110: 1105: 1102: 1099: 1096: 1093: 1090: 1087: 1082: 1079: 1076: 1071: 1068: 1065: 1061: 1057: 1054: 1049: 1045: 1041: 1038: 1032: 1028: 1024: 1021: 1016: 1012: 983: 979: 956: 952: 929: 925: 921: 918: 915: 908: 904: 900: 897: 894: 887: 883: 879: 876: 873: 860: 859: 855: 854: 842: 839: 833: 830: 827: 824: 821: 817: 808: 804: 799: 793: 789: 785: 782: 778: 773: 770: 767: 764: 761: 758: 753: 748: 745: 741: 737: 734: 731: 728: 725: 722: 717: 713: 689: 682: 678: 672: 668: 664: 661: 657: 652: 648: 644: 640: 620: 615: 612: 609: 606: 603: 600: 596: 592: 589: 586: 583: 580: 554: 547: 543: 537: 533: 529: 526: 522: 517: 513: 509: 505: 485: 480: 477: 474: 471: 468: 465: 461: 457: 454: 451: 448: 445: 434: 433: 428: 425: 424: 423: 412: 409: 403: 400: 397: 394: 391: 387: 381: 377: 374: 370: 367: 364: 361: 358: 353: 349: 343: 338: 335: 331: 326: 320: 315: 312: 308: 304: 301: 298: 295: 292: 281: 280: 276: 275: 264: 261: 255: 252: 249: 246: 243: 240: 236: 228: 224: 218: 214: 210: 207: 204: 201: 198: 195: 191: 186: 182: 178: 174: 171: 168: 165: 160: 155: 152: 148: 144: 141: 138: 135: 132: 129: 124: 120: 108: 107: 87: 84: 13: 10: 9: 6: 4: 3: 2: 2314: 2303: 2300: 2298: 2295: 2293: 2290: 2289: 2287: 2277: 2273: 2269: 2265: 2261: 2257: 2253: 2249: 2245: 2238: 2233: 2230: 2226: 2222: 2218: 2214: 2209: 2206: 2202: 2198: 2194: 2190: 2186: 2181: 2178: 2174: 2170: 2166: 2161: 2156: 2152: 2148: 2143: 2140: 2136: 2133: 2130: 2127: 2124: 2121: 2117: 2113: 2108: 2105: 2100: 2096: 2095: 2088: 2082: 2078: 2074: 2070: 2063: 2060: 2054: 2051: 2048: 2042: 2038: 2034: 2030: 2026: 2022: 2015: 2008: 2005: 2001: 1995: 1992: 1987: 1981: 1978: 1975: 1969: 1966: 1961: 1957: 1953: 1949: 1945: 1941: 1937: 1933: 1929: 1925: 1917: 1915: 1913: 1911: 1907: 1902: 1898: 1894: 1890: 1886: 1880: 1876: 1872: 1868: 1861: 1858: 1854: 1848: 1846: 1842: 1837: 1833: 1829: 1825: 1820: 1815: 1811: 1807: 1803: 1799: 1792: 1789: 1783: 1779: 1776: 1774: 1771: 1769: 1766: 1765: 1761: 1755: 1752: 1750: 1747: 1746: 1744: 1739: 1735: 1732: 1729: 1726: 1723: 1720: 1719: 1717: 1714: 1711: 1708: 1707: 1703: 1701: 1698: 1690: 1688: 1681: 1679: 1671: 1668: 1665: 1664: 1660: 1657: 1655:Low-frequency 1654: 1653: 1650: 1629: 1621: 1618: 1615: 1609: 1606: 1602: 1586: 1581: 1562: 1559: 1556: 1550: 1523: 1519: 1513: 1509: 1503: 1500: 1496: 1492: 1484: 1473: 1470: 1467: 1458: 1455: 1449: 1446: 1443: 1437: 1411: 1400: 1397: 1394: 1385: 1360: 1352: 1346: 1323: 1315: 1312: 1309: 1283: 1279: 1273: 1269: 1263: 1260: 1256: 1228: 1220: 1214: 1205: 1198: 1179: 1175: 1172: 1169: 1166: 1160: 1149: 1145: 1139: 1135: 1129: 1126: 1122: 1112: 1100: 1097: 1094: 1085: 1080: 1077: 1074: 1069: 1066: 1063: 1059: 1055: 1047: 1039: 1036: 1030: 1022: 1014: 1010: 1002: 1001: 1000: 981: 954: 927: 919: 916: 913: 906: 898: 895: 892: 885: 877: 874: 871: 857: 856: 840: 837: 831: 828: 825: 822: 819: 815: 806: 802: 797: 791: 787: 783: 780: 776: 768: 765: 762: 756: 743: 739: 735: 729: 726: 723: 715: 711: 703: 702: 701: 680: 676: 670: 666: 662: 659: 655: 646: 613: 610: 607: 604: 601: 598: 594: 587: 581: 570: 567:Applying the 545: 541: 535: 531: 527: 524: 520: 511: 478: 475: 472: 469: 466: 463: 459: 452: 446: 432:Spectrum Form 431: 430: 427:Modified form 426: 410: 407: 401: 398: 395: 392: 389: 385: 379: 375: 372: 365: 362: 359: 351: 347: 333: 329: 324: 310: 306: 302: 296: 290: 283: 282: 278: 277: 262: 259: 253: 250: 247: 244: 241: 238: 234: 226: 222: 216: 208: 205: 202: 196: 193: 189: 180: 169: 163: 150: 146: 142: 136: 133: 130: 122: 118: 110: 109: 105: 104: 103: 101: 97: 93: 85: 83: 80: 78: 73: 68: 66: 62: 58: 54: 50: 46: 42: 38: 34: 30: 27: 26: 19: 2250:(4): 14–38. 2247: 2243: 2216: 2212: 2192: 2188: 2176: 2150: 2146: 2138: 2068: 2062: 2053: 2024: 2020: 2007: 1999: 1994: 1980: 1968: 1927: 1923: 1866: 1860: 1852: 1801: 1797: 1791: 1733: 1727: 1721: 1704:Applications 1696: 1694: 1685: 1677: 1590: 1202: 861: 435: 95: 91: 89: 81: 71: 69: 56: 48: 44: 32: 28: 24: 23: 22: 2195:: 395–457. 2047:MATLAB file 2045:. See also 1543:Step5.IDFT( 1339:Step3.Move 106:S-Transform 2286:Categories 2219:: 85–102. 2147:Proc. IEEE 1784:References 86:Definition 2155:CiteSeerX 1952:1053-587X 1814:CiteSeerX 1622:τ 1619:− 1610:π 1607:− 1504:π 1501:− 1493:⋅ 1481:Δ 1408:Δ 1357:Δ 1320:Δ 1264:π 1261:− 1225:Δ 1130:π 1127:− 1109:Δ 1078:− 1060:∑ 1044:Δ 1027:Δ 978:Δ 951:Δ 924:Δ 914:α 903:Δ 882:Δ 841:α 829:α 826:π 788:α 784:π 781:− 769:α 752:∞ 747:∞ 744:− 740:∫ 663:π 660:− 614:τ 608:π 599:− 588:τ 528:π 525:− 479:τ 473:π 464:− 453:τ 402:τ 396:π 342:∞ 337:∞ 334:− 330:∫ 319:∞ 314:∞ 311:− 307:∫ 297:τ 263:τ 254:τ 248:π 239:− 209:τ 206:− 197:π 194:− 170:τ 159:∞ 154:∞ 151:− 147:∫ 29:transform 2272:13266737 2098:265–274. 1960:16074001 1901:29974786 1893:19163232 1836:30202517 1762:See also 942:, where 571:to both 2252:Bibcode 2029:Bibcode 1932:Bibcode 1806:Bibcode 70:A fast 2270:  2157:  2083:  1958:  1950:  1899:  1891:  1881:  1834:  1816:  700:gives 2268:S2CID 2240:(PDF) 2017:(PDF) 1956:S2CID 1897:S2CID 1832:S2CID 1715:(MRI) 2081:ISBN 1948:ISSN 1889:PMID 1879:ISBN 1302:for 864:Let 631:and 496:and 63:and 2260:doi 2221:doi 2197:doi 2165:doi 2116:doi 2073:doi 2037:doi 1940:doi 1871:doi 1824:doi 1378:to 2288:: 2266:. 2258:. 2246:. 2242:. 2217:23 2215:. 2193:24 2191:. 2187:. 2163:. 2151:77 2149:. 2114:. 2079:. 2035:. 2025:10 2023:. 2019:. 1954:. 1946:. 1938:. 1928:58 1926:. 1909:^ 1895:. 1887:. 1877:. 1844:^ 1830:. 1822:. 1812:. 1802:44 1800:. 102:. 79:. 67:. 2274:. 2262:: 2254:: 2248:8 2227:. 2223:: 2203:. 2199:: 2171:. 2167:: 2122:. 2118:: 2106:) 2089:. 2075:: 2043:. 2039:: 2031:: 1962:. 1942:: 1934:: 1903:. 1873:: 1853:S 1838:. 1826:: 1808:: 1740:. 1734:S 1728:S 1722:S 1697:S 1637:) 1630:2 1626:) 1616:t 1613:( 1603:e 1599:( 1566:] 1563:p 1560:, 1557:m 1554:[ 1551:B 1524:2 1520:m 1514:2 1510:p 1497:e 1490:] 1485:F 1477:) 1474:m 1471:+ 1468:p 1465:( 1462:[ 1459:X 1456:= 1453:] 1450:p 1447:, 1444:m 1441:[ 1438:B 1417:] 1412:F 1404:) 1401:m 1398:+ 1395:p 1392:( 1389:[ 1386:X 1366:] 1361:F 1353:p 1350:[ 1347:X 1324:F 1316:m 1313:= 1310:f 1284:2 1280:m 1274:2 1270:p 1257:e 1234:] 1229:F 1221:p 1218:[ 1215:X 1180:N 1176:n 1173:p 1170:2 1167:j 1161:e 1150:2 1146:m 1140:2 1136:p 1123:e 1118:] 1113:F 1104:) 1101:m 1098:+ 1095:p 1092:( 1089:[ 1086:X 1081:1 1075:N 1070:0 1067:= 1064:p 1056:= 1053:) 1048:F 1040:m 1037:, 1031:T 1023:n 1020:( 1015:x 1011:S 982:F 955:T 928:F 920:p 917:= 907:F 899:m 896:= 893:f 886:T 878:n 875:= 872:t 853:. 838:d 832:t 823:2 820:j 816:e 807:2 803:f 798:/ 792:2 777:e 772:) 766:+ 763:f 760:( 757:X 736:= 733:) 730:f 727:, 724:t 721:( 716:x 712:S 688:) 681:2 677:f 671:2 667:t 656:e 651:| 647:f 643:| 639:( 619:) 611:f 605:2 602:j 595:e 591:) 585:( 582:x 579:( 565:. 553:) 546:2 542:f 536:2 532:t 521:e 516:| 512:f 508:| 504:( 484:) 476:f 470:2 467:j 460:e 456:) 450:( 447:x 444:( 411:f 408:d 399:f 393:2 390:j 386:e 380:] 376:t 373:d 369:) 366:f 363:, 360:t 357:( 352:x 348:S 325:[ 303:= 300:) 294:( 291:x 260:d 251:f 245:2 242:j 235:e 227:2 223:f 217:2 213:) 203:t 200:( 190:e 185:| 181:f 177:| 173:) 167:( 164:x 143:= 140:) 137:f 134:, 131:t 128:( 123:x 119:S 96:S 92:S 72:S 57:S 49:S 45:S 33:S 25:S 20:.

Index

Laplace transform
short-time Fourier transform
continuous wavelet transform
Gabor transform
Wigner distribution function
Cohen's class distribution function
open source license
Gaussian function
Fourier transform
Magnetic resonance imaging
multiresolution analysis
Reflection seismology
Global seismology
Laplace transform
Wavelet transform
Short-time Fourier transform
Bibcode
1996ITSP...44..998S
CiteSeerX
10.1.1.462.1500
doi
10.1109/78.492555
S2CID
30202517


doi
10.1109/IEMBS.2008.4649729
ISBN
978-1-4244-1814-5

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