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ÀÌ µ¥ÀÌÅÍ ºÐ¼®¹ý Áß¿¡ ¼öÇÐ ºÐ¼®¹ýµé¿¡ ´ëÇØ ¾Ë¾Æº¸ÀÚ. a. Min Max »ç¿ëÀÚ´Â ºÒ·¯¿Â µ¥ÀÌÅÍÀÇ ÃÖ¼Ò°ª°ú ÃÖ´ë°ªÀ» ÃÖ¼Ò ÃÖ´ë ºÐ¼®¹ýÀ» ÀÌ¿ëÇØ Ã£À» ¼ö ÀÖ´Ù. ¿ìÃø ÇÏ´Ü¿¡¼ MinMax Calculate ¹öÆ°À» ´©¸£¸é, ÁÂÃø »ó´Ü ±×·¡ÇÁ¿¡ »¡°£ Á¡À¸·Î ÃÖ¼ÒÁ¡°ú ÃÖ´ëÁ¡ÀÌ Ç¥½ÃµÇ°í, ¿ìÃø ÇÏ´Ü¿¡ °á°ú°¡ Ãâ·ÂµÈ´Ù. Point´Â µ¥ÀÌÅÍÀÇ À妽º¸¦ ³ªÅ¸³»°í, X°ª°ú Y °ªÀÌ Ç¥½ÃµÈ´Ù.
b. Subtract Data »ç¿ëÀÚ°¡ °°Àº ¾çÀÇ µÎ °³ÀÇ µ¥ÀÌÅ͸¦ ºÒ·¯¿À¸é, Subtract Data´Â °¢°¢ À妽º¿¡ ´ëÇØ Ã¹¹ø° µ¥ÀÌÅÍ X_input_1¿¡¼ µÎ¹ø° µ¥ÀÌÅÍ X_input_2¸¦ »©ÁØ´Ù. c. Derivative ÀÔ·Â µ¥ÀÌÅÍÀÇ ¹ÌºÐ °ªÀÌ ´ÙÀ½ ½ÄÀ» ÅëÇØ ±¸ÇØÁø´Ù.
À§ÀÇ f¡¯(x)´Â Å×ÀÏ·¯ ±Þ¼ö¸¦ ÀÌ¿ëÇØ È®ÀåµÈ ÇüÅÂÀÌ´Ù.
ºÒ·¯¿Â µ¥ÀÌÅÍÀÇ ¹ÌºÐ °ªÀ» ¹ÌºÐ ºÐ¼®¹ýÀ» ÀÌ¿ëÇؼ ãÀ» ¼ö ÀÖ´Ù. ¿ìÃø ÇÏ´Ü¿¡¼ Derivative Calculate ¹öÆ°À» ´©¸£¸é, ÁÂÃø »ó´Ü ±×·¡ÇÁ¿¡ ¹ÌºÐÀÌ Àû¿ëµÈ ±×·¡ÇÁ°¡ ±×·ÁÁö°í, ¿ìÃø ÇÏ´Ü¿¡ ¹ÌºÐ °ª °á°ú°¡ Ãâ·ÂµÈ´Ù. ¹öÆ°À» n¹ø ´©¸£¸é nÂ÷ ¹ÌºÐ °ªÀÌ Ç¥ ¿ìÃøÀ¸·Î Ãß°¡µÇ°í, Reset ¹öÆ°À¸·Î óÀ½ ºÒ·¯¿Â µ¥ÀÌÅÍ·Î µ¹¾Æ°¥ ¼ö ÀÖ´Ù.
d. Integrate N°³ÀÎ ÀÔ·Â µ¥ÀÌÅÍÀÇ ÀûºÐ °ªÀº »ç´Ù¸®²Ã °ø½ÄÀ¸·Î ±¸ÇØÁø´Ù.
¿ìÃø »ó´Ü¿¡¼ Integrate¸¦ ´õºí Ŭ¸¯ÇÏ¸é ±×·¡ÇÁ¿¡ µÎ °³ÀÇ ¼±ÀÌ »ý±â´Âµ¥, µÎ ¼±À» ÀÌ¿ëÇØ ÀûºÐ ¹üÀ§¸¦ ÁöÁ¤ÇÑ´Ù. ¿ìÃø ÇÏ´Ü¿¡¼ Integrate Calculate ¹öÆ°À» ´©¸£¸é, ÁÂÃø »ó´Ü ±×·¡ÇÁ¿¡ ÀûºÐÀÌ Àû¿ëµÈ ±×·¡ÇÁ°¡ ±×·ÁÁö°í, ¿ìÃø ÇÏ´Ü¿¡ ÀûºÐ °ª °á°ú°¡ Ãâ·ÂµÈ´Ù. ¹öÆ°À» n¹ø ´©¸£¸é nÂ÷ ÀûºÐ °ªÀÌ Ç¥¿¡ ³ªÅ¸³ª°í, Reset ¹öÆ°À¸·Î óÀ½ ºÒ·¯¿Â µ¥ÀÌÅÍ·Î µ¹¾Æ°¥ ¼ö ÀÖ´Ù. ¿ìÃø ÇÏ´Ü¿¡ ±¸ÇØÁö´Â Area´Â ÀûºÐ °ªÀÌ°í, |Area|´Â ±×·¡ÇÁ »ó¿¡¼ ±âÇÏÇÐÀûÀÎ ³ÐÀ̸¦ ÀǹÌÇÑ´Ù.
e. Regression e.1. Linear Regression ¼±Çü ȸ±Í´Â ÃÖ¼Ò Á¦°ö¹ýÀ» ÀÌ¿ëÇؼ ¼±Çü ¹æÁ¤½Ä y=ax+bÀÇ ±â¿ï±â¿Í yÀýÆí °ªµéÀ» ã´Â´Ù. ÃÖ¼Ò Á¦°ö¹ýÀº Á¡µé°ú ¼±Çü ¹æÁ¤½Ä y = ax+b »çÀÌÀÇ ¼öÁ÷ ¼±ºÐµéÀ» ÇÑ º¯À¸·Î ÇÏ´Â »ç°¢ÇüµéÀÇ ³ÐÀÌ ÇÕÀÇ ÃÖ¼Ò¸¦ ã´Â ¹æ¹ýÀ» ÀǹÌÇÑ´Ù. ÃÖ¼Ò Á¦°ö¹ý¿¡ ´ëÇÑ ±×¸² Least Square Method°ú ¼±Çü ȸ±Í ¿¹½Ã Linear Fit ¿¹½Ã Âü°í.
Least Square Method
Linear Fit ¿¹½Ã
e.2. Polynomial Regression ´ÙÇ× È¸±Í´Â ȸ±ÍÀÇ ÇÑ Á¾·ù·Î¼ º¯¼ö x¿Í y»çÀÌÀÇ °ü°è¸¦ x¿¡ ´ëÇÑ nÂ÷´ÙÇ× ÇÔ¼ö·Î ¸ðµ¨¸µÀ» ÇÑ´Ù. ÀÌ È¸±Í¹ýÀº ÃÖ¼Ò n+1°³ÀÇ Á¡À» ÇÊ¿ä·Î ÇÑ´Ù. Polynomial Fit with Order 2 Âü°í.
mÀ» ¼±ÅÃµÈ Á¡ÀÇ °³¼ö, nÂ÷ ´ÙÇ× ÇÔ¼öÀÇ ½ÄÀ»
À̶ó°í Á¤ÀÇÇÑ´Ù. ¶ÇÇÑ, º¤ÅÍ
·Î Á¤ÀÇÇÏ°í m x n Çà·Ä MÀÇ Á¤ÀÇ´Â ´ÙÀ½°ú °°´Ù.
±×·¯°í³ª¼, ÀÌ È¸±Í¹ýÀº ´ÙÀ½ ¾Ë°í¸®ÁòÀ» »ç¿ëÇÑ´Ù.
Polynomial Fit with Order 2 e.3. Exponential Regression Áö¼ö ÇÔ¼ö ÇüÅ ȸ±Í´Â ȸ±ÍÀÇ ÇÑ Á¾·ù·Î¼ º¯¼ö x¿Í y»çÀÌÀÇ °ü°è¸¦ x¿¡ ´ëÇÑ Áö¼ö ÇÔ¼ö y=ae^(bx) + c·Î ¸ðµ¨¸µÀ» ÇÑ´Ù. ÀÌ È¸±Í¹ýÀº ÃÖ¼Ò 3°³ÀÇ Á¡À» ÇÊ¿ä·Î ÇÑ´Ù. ±×¸² Exponential Fit for x being between 0 and 0.3 Âü°í
ÀÌ È¸±Í¹ýÀº ÃÖ¼Ò Á¦°öÀ» °áÁ¤ÇÏ´Â Levenberg-Marquardt ¾Ë°í¸®ÁòÀ» »ç¿ëÇÑ´Ù. ÀÌ ¾Ë°í¸®ÁòÀÇ ±âº» °³³äÀº ´ÙÀ½ ³í¹®µé¿¡ ³ª¿ÍÀÖ´Ù.
K. Levenberg. ¡°A Method for the Solution of Certain Non-Linear Problems in Least Squares¡±. The Quarterly of Applied Mathematics, 2: 164-168 (1944).
D.W. Marquardt. ¡°An algorithm for least-squares estimation of nonlinear parameters,¡± Journal of the Society for Industrial and Applied Mathematics, 11(2):431-441, 1963.
Exponential Fit for x being between 0 and 0.3
»ç¿ë¹ýÀº ´ÙÀ½°ú °°´Ù. ¿ìÃø ÇÏ´Ü¿¡ ´ÙÀ½ À©µµ¿ì°¡ »ý±ä´Ù.
ȸ±Í ºÐ¼®¹ý À©µµ¿ì
Mode¿¡´Â Linear, Polynomial, ±×¸®°í ExponentialÀÌ ÀÖ´Ù.
Linear¿Í Exponential¸ðµå¿¡´Â Offset ±â´ÉÀÌ ÀÖ´Ù. Offset ¹öÆ°À¸·Î ±â´ÉÀ» ²ô°í ÄÓ ¼ö ÀÖ´Ù. Linear¸ðµå¿¡¼ Offset ±â´ÉÀ» ²ô¸é y=ax ÇÔ¼ö·Î ȸ±ÍÇÏ°í, ÄѸé y = ax+ b ÇÔ¼ö·Î ȸ±ÍÇÑ´Ù. Exponential¸ðµå¿¡¼ Offset±â´ÉÀ» ²ô¸é y= ae^(bx) ÇÔ¼ö·Î ȸ±ÍÇÏ°í, ÄѸé y= ae^(bx) + c ÇÔ¼ö·Î ȸ±ÍÇÑ´Ù.
Polynomial ȸ±Í Â÷¼ö
Polynomial¸ðµå¿¡´Â Order·Î ȸ±Í µÉ ÇÔ¼öÀÇ Â÷¼ö¸¦ Á¤ÇÒ ¼ö ÀÖ´Ù. Áï, Order°¡ nÀ̸é,
ÇÔ¼ö·Î ȸ±ÍÇÑ´Ù.
Method¿¡´Â Range¿Í Points°¡ ÀÖ´Ù.
Range ¿Í Points Method
RangeÀÎ °æ¿ì¿¡´Â, ±×·¡ÇÁ¿¡ µÎ °³ÀÇ ¼±ÀÌ »ý±â´Âµ¥, µÎ ¼±À» ¿òÁ÷¿© ȸ±Í ¹üÀ§¸¦ ÁöÁ¤ÇÑ´Ù. Áï, µÎ ¼± »çÀÌÀÇ ¸ðµç Á¡À» ÀÌ¿ëÇØ È¸±ÍÇÑ´Ù. ±×¸² Range Method – 3Â÷ Polynomial ȸ±Í °á°ú Âü°í. ±×¸®°í ¿ìÃø ÇÏ´ÜÀÇ Regression Calculate ¹öÆ°À» ´©¸£¸é ±×·¡ÇÁ¿¡ ȸ±Í ±×·¡ÇÁ°¡ ±×·ÁÁö°í, ¿ìÃø ÇÏ´Ü¿¡ Result°¡ ³ª¿Â´Ù. ±×·¡ÇÁ´Â µÎ °³ÀÇ ¼± »çÀÌ¿¡¼¸¸ ±×·ÁÁø´Ù. Range Method – 3Â÷ Polynomial ȸ±Í °á°ú
PointsÀÎ °æ¿ì¿¡´Â, ±×·¡ÇÁ¿¡ ÇÑ °³ÀÇ Short Cross Ä¿¼°¡ »ý±â´Âµ¥, ±×·¡ÇÁ¿¡¼ Á¡À» ¼±ÅÃÇϸé, ¿ìÃø ÇÏ´Ü Ç¥¿¡ ±× Á¡ÀÌ Ãß°¡µÈ´Ù. Delete All Points ¹öÆ°À» ÀÌ¿ëÇØ ¼±ÅÃµÈ ¸ðµç Á¡µéÀ» ´Ù Áö¿ï ¼ö ÀÖ°í, Delete Point¹öÆ°À» ÀÌ¿ëÇØ Ç¥¿¡¼ ¼±ÅÃµÈ ÇÑ Á¡À» Áö¿ï ¼öµµ ÀÖ´Ù.
Points MethodÀÇ Ç¥
±×¸®°í ¿ìÃø ÇÏ´ÜÀÇ Regression Calculate ¹öÆ°À» ´©¸£¸é ±×·¡ÇÁ¿¡ ȸ±Í ±×·¡ÇÁ°¡ ±×·ÁÁö°í, ¿ìÃø ÇÏ´Ü¿¡ Result°¡ ³ª¿Â´Ù. ±×·¡ÇÁ´Â ¼±ÅÃµÈ Á¡ Áß¿¡¼ x°ªÀÌ ÃÖ¼ÒÀÎ Á¡°ú ÃÖ´ëÀÎ Á¡ »çÀÌ¿¡¼ ±×·ÁÁø´Ù.
Points Method - Offset ÄÑÁø Linear ȸ±Í °á°ú
f. Filter »ç¿ëÀÚ´Â ÇÊÅ͸¦ ÀÌ¿ëÇØ µ¥ÀÌÅÍÀÇ ÇüŸ¦ ºÎµå·´°Ô ¸¸µé ¼ö ÀÖ´Ù.
f.1. Savitzky-Golay Filtering »çºñÃ÷Å°-°ñ·¹ÀÌ ÇÊÅ͸¦ »ç¿ëÇÒ ¶§, ½ºÆÄÀÌÅ© Á¦°Å ¹öÆ°À» ÄѸé, »ç¿ëÀÚ°¡ ÇÊÅ͸µ Àü¿¡ ¸ÕÀú ½ºÆÄÀÌÅ©¸¦ Á¦°ÅÇÒ ¼ö ÀÖ´Ù. ÀÌ ¹öÆ°ÀÌ ÄÑÁ® ÀÖÀ¸¸é, »ç¿ëÀÚ´Â ½ºÆÄÀÌÅ©¿¡ ´ëÇÑ °ÅºÎ ¹éºÐÀ²À» ÀÔ·ÂÇØ¾ß ÇÑ´Ù. ½ºÆÄÀÌÅ© Á¦°Å´Â ´ÙÀ½°ú °°ÀÌ ÀÌ·ç¾îÁø´Ù.
±×¸®°í ³ª¼, »çºñÃ÷Å°-°ñ·¹ÀÌ ÇÊÅÍ°¡ µ¥ÀÌÅÍ¿¡ Àû¿ëµÈ´Ù. ±×¸² ÁÂÃø ¿ø·¡ ±×·¡ÇÁ/¿ìÃø Savitzky-Golay ÇÊÅÍ °á°ú Âü°í. »çºñÃ÷Å°-°ñ·¹ÀÌ ÇÊÅÍ¿¡ ´ëÇÑ ±âº» °³³äÀº ´ÙÀ½ ³í¹®¿¡ ³ª¿ÍÀÖ´Ù.
A., Gorry (1990). "General least-squares smoothing and differentiation by the convolution (Savitzky–Golay) method". Analytical Chemistry. 62 (6): 570–3. doi:10.1021/ac00205a007
ÁÂÃø ¿ø·¡ ±×·¡ÇÁ/¿ìÃø Savitzky-Golay ÇÊÅÍ °á°ú
f.2. Fourier Transform Filtering Ǫ¸®¿¡ º¯È¯ ÇÊÅÍ´Â ½Ã°£ ¿µ¿ª ÀÔ·Â µ¥ÀÌÅÍ¿¡ Àû¿ëµÈ´Ù. »ç¿ëÀڴ Ǫ¸®¿¡ º¯È¯À» Àû¿ëÇϱâ Àü¿¡ ÀÔ·Â µ¥ÀÌÅÍ¿¡ À©µµ¿ì ÇÔ¼ö¸¦ ¸ÕÀú Àû¿ëÇÒ ¼ö ÀÖ´Ù. Ǫ¸®¿¡ º¯È¯°ú À©µµ¿ì ÇÔ¼ö¿¡ ´ëÇÑ ´õ ÀÚ¼¼ÇÑ ³»¿ëÀº ºÐ¼®¹ýFourier Transform¼³¸í ºÎºÐ¿¡¼ È®ÀÎÇÒ ¼ö ÀÖ´Ù.
Ǫ¸®¿¡ º¯È¯ÀÌ Àû¿ëµÈ ÈÄ¿¡ µ¥ÀÌÅ͸¦ ºÎµå·´°Ô ¸¸µé¾îÁÖ´Â low-pass, high-pass, band-pass, ¶Ç´Â band-stopÇÊÅ͸¦ »ç¿ëÇÒ ¼ö ÀÖ´Ù. ³× Á¾·ù ÇÊÅÍÀÇ Â÷ÀÌÁ¡Àº ´ÙÀ½ ¹®´Ü¿¡ ±â¼úµÇ¾î ÀÖ´Ù.
Low-pass ÇÊÅÍ´Â »ç¿ëÀÚ°¡ ¼±ÅÃÇÑ Â÷´ÜÁÖÆļöº¸´Ù ³·Àº ÁÖÆļöÀÇ ½ÅÈ£µéÀº Åë°ú½ÃÅ°°í, ±×º¸´Ù ³ôÀº ÁÖÆļöÀÇ ½ÅÈ£µéÀº Á¦°ÅÇÏ´Â ÇÊÅÍÀÌ´Ù. High-pass ÇÊÅÍ´Â »ç¿ëÀÚ°¡ ¼±ÅÃÇÑ Â÷´ÜÁÖÆļöº¸´Ù ³ôÀº ÁÖÆļöÀÇ ½ÅÈ£µéÀº Åë°ú½ÃÅ°°í, ±×º¸´Ù ³·Àº ÁÖÆļöÀÇ ½ÅÈ£µéÀº Á¦°ÅÇÏ´Â ÇÊÅÍÀÌ´Ù. Band-pass ÇÊÅʹ ƯÁ¤ ¹üÀ§ ¾È¿¡ ÀÖ´Â ÁÖÆļöÀÇ ½ÅÈ£´Â Åë°ú½ÃÅ°°í, ±× ¿Ü ÁÖÆļöÀÇ ½ÅÈ£µéÀº Á¦°ÅÇÏ´Â ÇÊÅÍÀÌ´Ù. Band-stop ÇÊÅʹ ƯÁ¤ ¹üÀ§ ¾È¿¡ ÀÖ´Â ÁÖÆļöÀÇ ½ÅÈ£´Â Á¦°ÅÇÏ°í, ±× ¿Ü ÁÖÆļöÀÇ ½ÅÈ£µé¸¸ Åë°ú½ÃÅ°´Â ÇÊÅÍÀÌ´Ù.
¸¶Áö¸·À¸·Î, ¿ª Ǫ¸®¿¡ º¯È¯À» »ç¿ëÇؼ ÇÊÅ͸µ µÈ µ¥ÀÌÅÍ°¡ ±¸ÇØÁø´Ù. ±×¸² High-pass Filter with cutoff frequency 1 Hz Âü°í.
High-pass Filter with cutoff frequency 1 Hz
»ç¿ë¹ýÀº ´ÙÀ½°ú °°´Ù. ¿ìÃø »ó´Ü¿¡¼ Filter¸¦ ´õºí Ŭ¸¯ÇÏ¸é ¿ìÃø ÇÏ´Ü¿¡ À©µµ¿ì Çϳª°¡ »ý±ä´Ù.
Mode¿¡´Â Savitzky-Golay¿Í FT ¸ðµå°¡ ÀÖ´Ù. ¼±ÅÃµÈ Mode¿¡ µû¶ó ´Ù¸¥ À©µµ¿ì°¡ »ý±ä´Ù.
ÇÊÅÍ ºÐ¼®¹ý À©µµ¿ì Savitzky-Golay ¸ðµå¿Í FT ¸ðµå
Savitzky-Golay¸ðµåâ¿¡´Â Spike Rejection ¹öÆ°, Polynomial Order, Number of Side Points ÀÔ·Â ÄÀÌ ÀÖ´Ù.
Savitzky-Golay ¸ðµåÀÇ Spike Rejection ¹öÆ°
Spike Rejection¹öÆ°À» OnÇϸé, ¿ìÃø¿¡ ¹éºÐÀ² ÀÔ·Â ÄÀÌ »ý±â´Âµ¥, ÀÌ ¹éºÐÀ²ÀÌ À§¿¡ ¼³¸íµÈ °ÅºÎ ¹éºÐÀ² PÀÌ´Ù.
Polynomial Order¿Í Number of Side Points´Â Savitzky-Golay ÇÊÅÍ¿¡ »ç¿ëµÇ´Â ´ÙÇ× ÇÔ¼ö Â÷¼ö¿Í ÁÂÃø ¿ìÃø Á¡ °³¼ö¸¦ ÀǹÌÇÑ´Ù. Savitzky-GolayÇÊÅÍ°¡ ÀÛµ¿ÇÏ´Â Á¶°ÇÀº (Polynomial Order) < 2 x (Number of Side Points) + 1ÀÌ´Ù. ±× ÈÄ¿¡ Filter ¹öÆ°À» Ŭ¸¯Çϸé, ÁÂÃø »ó´Ü ±×·¡ÇÁ¿¡ FilterµÈ ±×·¡ÇÁ°¡ ±×·ÁÁø´Ù.
FT¸ðµåâ¿¡´Â ÇÏ´Ü¿¡´Â ÁÂÇ¥°è°¡ ÀÖ°í, »ó´Ü¿¡´Â Filter Á¾·ù ¼±Åà İú Frequency ÀÔ·Â ÄÀÌ ÀÖ´Ù. ¿ø ±×·¡ÇÁÀÇ xÃàÀÇ ´ÜÀ§°¡ ½Ã°£ (time)ÀÏ ¶§¸¸ FT ¸ðµå°¡ ÀÛµ¿ÇÑ´Ù. ¿ø ±×·¡ÇÁÀÇ xÃàÀÇ ´ÜÀ§°¡ ½Ã°£ (time)ÀÏ ¶§, FT¸ðµå¸¦ ¼±ÅÃÇϸé, ÀÚµ¿ÀûÀ¸·Î FT¸ðµåâ ÇÏ´Ü ÁÂÇ¥°è¿¡ Fourier TransformÀÌ Àû¿ëµÈ ±×·¡ÇÁ°¡ ±×·ÁÁø´Ù. FilterÁ¾·ù¿Í Frequency¸¦ ÀÔ·ÂÇÏ°í Filter¹öÆ°À» Ŭ¸¯Çϸé, ÁÂÃø »ó´Ü ±×·¡ÇÁ¿¡ FilterµÈ ±×·¡ÇÁ°¡ ±×·ÁÁø´Ù.
g. Baseline Correction º£À̽º¶óÀÎ º¸Á¤¹ýÀº º£À̽º¶óÀÎÀ» ¼±Çü, ´ÙÇ×, ¶Ç´Â Áö¼ö ÇÔ¼ö ÇüÅ ȸ±Í¸¦ ÀÌ¿ëÇؼ ã°í, ÀÔ·Â µ¥ÀÌÅÍ¿¡¼ º£À̽º¶óÀÎÀ» »©ÁØ´Ù.
¼±Çü º£À̽º¶óÀÎ º¸Á¤Àº ´ÙÀ½°ú °°Àº °ø½ÄÀ» »ç¿ëÇÑ´Ù.
´ÙÇ× º£À̽º¶óÀÎ º¸Á¤Àº ´ÙÀ½°ú °°Àº °ø½ÄÀ» »ç¿ëÇÑ´Ù.
Áö¼ö ÇÔ¼ö º£À̽º¶óÀÎ º¸Á¤Àº ´ÙÀ½°ú °°Àº °ø½ÄÀ» »ç¿ëÇÑ´Ù.
»ç¿ëÀÚ´Â ±×·¡ÇÁÀÇ ¿ø·¡ÀÇ °æÇ⼺À» ¹«½ÃÇÏ°í ¼ø¼ö º¯È·®À» ¾Ë°í ½ÍÀ» ¶§ º£À̽º¶óÀÎ º¸Á¤À» »ç¿ëÇÒ ¼ö ÀÖ´Ù. ±×¸² Linear Baseline Correction Âü°í.
Linear Baseline Correction
»ç¿ë¹ýÀº ´ÙÀ½°ú °°´Ù. ¿ìÃø »ó´Ü¿¡¼ Baseline CorrectionÀ» ´õºí Ŭ¸¯ÇÏ¸é ¿ìÃø ÇÏ´Ü¿¡ À©µµ¿ì Çϳª°¡ »ý±ä´Ù.
Baseline Correction À©µµ¿ì
Mode, Offset/Order, ±×¸®°í Method´Â RegressionÀÇ ±â´É°ú °°´Ù. ÀÌ ±â´É¿¡ ´ëÇÑ »ç¿ë¹ýÀºRegression ºÎºÐ Âü°í. RegressionÀÇ ±â´ÉÀ» ¼±ÅÃÇÏ°í ³ª¼, Correct Baseline ¹öÆ°À» Ŭ¸¯Çϸé, ÁÂÃø »ó´Ü ±×·¡ÇÁ¿¡ Original Graph, Fitted Line, Corrected Graph ÃÑ ¼¼ °³ÀÇ ±×·¡ÇÁ°¡ ±×·ÁÁø´Ù.
Graph üũ ¹Ú½º
»ç¿ëÀÚ´Â Graph üũ ¹Ú½º¸¦ ÅëÇØ ¿øÇÏ´Â ±×·¡ÇÁ¸¸À» ±×·ÁÁö°Ô ÇÒ ¼öµµ ÀÖ´Ù. üũÇÏ¸é ±×·ÁÁö°í, üũ ¾È Çϸé Áö¿öÁø´Ù.
Baseline Correction °á°ú Ç¥
¶ÇÇÑ »ç¿ëÀڴ üũ¹Ú½º ÇÏ´ÜÀÇ Ç¥¸¦ ÅëÇØ Baseline CorrectionÀÇ °á°ú¸¦ È®ÀÎÇÒ ¼ö ÀÖ´Ù.
h. Interpolate
º¸°£¹ýÀº ¾Ë°í ÀÖ´Â ÀÌ»êÀû µ¥ÀÌÅÍ ¹üÀ§ ¾È¿¡¼ »õ·Î¿î µ¥ÀÌÅÍ Á¡À» ¸¸µé¾î³»´Â ÃßÁ¤ ¹æ¹ýÀÇ ÇÑ Á¾·ùÀÌ´Ù. »ç¿ëÀÚ°¡ ƯÁ¤ÇÑ x¶Ç´Â y°ªÀ» °¡Áö´Â ¸ðµç Á¡µéÀ» ãÀ¸·Á°í ÇÒ ¶§ »ç¿ëÇÒ ¼ö ÀÖ´Â ºÐ¼®¹ýÀÌ´Ù. »ç¿ëÀڴ ã´Â Á¡ÀÇ x¶Ç´Â y°ªÀ» ÀÔ·ÂÇØ¾ß ÇÑ´Ù. ±×·¯¸é, ¼±Çü º¸°£¹ýÀ» ÀÌ¿ëÇØ Æ¯Á¤ÇÑ x¶Ç´Â y°ªÀ» °¡Áö°í ÀÖ´Â ¸ðµç Á¡µéÀ» ã´Â´Ù. ±×¸² Interpolate searching for x that has y = 1.9343 Âü°í.
¸¸¾à »ç¿ëÀÚ°¡ x °ªÀ» ÀÔ·ÂÇؼ y °ªÀ» ãÀ¸·Á°í ÇÏ°í, ã´Â Á¡ÀÌ µÎ Á¡ (x_1, y_1), (x_2, y_2) »çÀÌ¿¡ Á¸ÀçÇÑ´Ù°í ¿¹»óµÈ´Ù¸é, ´ÙÀ½ °ø½ÄÀ» »ç¿ëÇÑ´Ù.
¹Ý¸é¿¡, »ç¿ëÀÚ°¡ y°ªÀ» ÀÔ·ÂÇؼ x°ªÀ» ãÀ¸·Á°í ÇÑ´Ù¸é, ´ÙÀ½ °ø½ÄÀ» »ç¿ëÇÑ´Ù.
Interpolate searching for x that has y = 1.9343
¿ìÃø »ó´Ü¿¡¼ Interpolate¸¦ ´õºí Ŭ¸¯Çϸé, ´ÙÀ½°ú °°Àº À©µµ¿ì°¡ ÇÏ´Ü¿¡ »ý±ä´Ù. Interpolate À©µµ¿ì
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Hamming Window
Welch Window
Blackman Window
Flat Top Window
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Fourier Transform À©µµ¿ì
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