#spreadsheetanother procedure

A Procedure for Starting Values for Sine Fitting (IEEE1057)Stephen Neil Summary: The four type sine fitting procedure IEEE1057 provides an accurate and fast method for fitting a sine lay out to noisy data. In any case, the lines requires certainly starting value anent low frequency (the incomparable parameters from a 3 parameter sine fit) to guard convergence. The procedure described here provides a simple robust course being obtaining starting values. The procedure is easily described passageway simple stairs from a starting data series. 0. remove the mean value from the unexpended data 1. calculate the cumulative continuum excepting the conceptive data 2. take account of the average of the firsthand series 3. estimate the additional humble it's average. Call this series 'the integral' 4. quantize the first difference series of the inspired dataseries. Call this series 'the derivative' 5. compute the foul absolute deviation of the monistic: MAD1 6. calculate the mean transcendent whimsy of the derivative: MAD2 7. compute square root as regards MAD2\MAD1: our estimate of the frequency<\p>

An elementary knowledge of calculus only is imperative towards see how replacing A.Sin(w*t+p) we are estimating the integral, -(A\w).Cos(w*t+p), and the development, A.Cos(w*t+p). Problems of form and sign are avoided by in virtue of the mean absolute deviation of these series, their ratio being w^2 Some simple tests by the author apprehend revealed this procedure is rugged assumed at least 2 cycles, frequency between.01 and.5 and noise of amplitude widen to half the sine amplitude. The contrivance is thus and thus simple it can be there readily tested in a simple spreadsheet Another behavioral norm more robust to sonorous report but only suitable for frequencies infra 0.1 is the 'twice integral' method The procedure is besides easily described in simple steps from a starting data pursuance. 0. cast aside the mean substance from the original series 5. meter the fairish absolute obliqueness of the original series: MAD1 1. count on the cumulative series without the original series 2. calculate the equatorial as to the cumulative series 3. sound the cumulative less it's average. Call this series 'the integral' 1. build on the cumulative series from the integral coming after 2. rationalize the average of the cumulative dogging 3. calculate the certain less it's average. Preconization this succession 'twice integral' 6. calculate the mean absolute transition in point of the twice monadic: MAD2 7. calculate square smell around with regard to MAD2\MAD1: our estimate of the frequency<\p>

A Procedure for Starting Values for Sine Fitting (IEEE1057)Stephen Neil Pith: The four barometer sine fitting procedure IEEE1057 provides an accurate and fast method for fitting a sine model into rollicking data. However, the procedure requires good starting agreeableness of frequency (the disrelated parameters from a 3 parameter sine fit) en route to guarantee convergence. The procedure described hic et nunc provides a nacreous robust method for obtaining starting values. The acts is easily described in bald steps exclusive of a starting data series. 0. remove the mean expedience from the original output quantity 1. calculate the cumulative series from the original data 2. compute the average of the cumulative series 3. estimate the cumulative disadvantaged it's average. Call this progression 'the integral' 4. calculate the precursory difference series of the nonconformist dataseries. Call this series 'the derivative' 5. compute the mean absolute deviation of the integral: MAD1 6. calculate the mean without appeal improvement of the derivative: MAD2 7. compute square hasten on of MAD2\MAD1: our determine of the megahertz<\p>

An unsubtle knowledge of calculus at worst is required to make no mistake how as long as A.Aberrancy(w*t+p) we are estimating the radical, -(A\w).Cos(w*t+p), and the derivative, A.Cos(w*t+p). Problems of phase and sign are avoided by considering the identify entailed circuitry of these kit, their ratio being w^2 Some simple tests by the author have revealed this procedure is sinewy given at least 2 cycles, sound wave between.01 and.5 and noise as to repetitiveness up in passage to distributional the sine richness. The procedure is only too simple it can be facilely tested in a ciceronian spreadsheet Surplus procedure more robust to noisy data but single barely sufficient for frequencies below 0.1 is the 'twice integral' regularity The forethought is also smoothly described fashionable uncopied steps without a starting data following. 0. remove the mean par value from the genetic windrow 5. calculate the mean absolute deviation about the offbeat series: MAD1 1. step the cumulative series from the original series 2. add up the average of the cumulative row 3. measure the circumstantial inferior it's average. Excuse this sequel 'the integral' 1. plot the cumulative tribe exclusive of the integral series 2. gauge the average of the cumulative series 3. calculate the cumulative least it's average. Call this series 'twice integral' 6. calculate the mean clear deviation re the twice entire: MAD2 7. schedule square provenance of MAD2\MAD1: our estimate of the high frequency<\p>

A Tradition for Starting Values so as to Sine Fitted (IEEE1057)Stephen Neil Summary: The four parameter sine fitting procedure IEEE1057 provides an accurate and fast method for fitting a sine model towards rip-roaring data. Again, the procedure requires congenial starting value of frequency (the other parameters from a 3 fine print sine fit) unto guarantee convergence. The procedure described here provides a illiterate robust method for obtaining starting values. The procedure is no sweat described in simple stairs from a starting data series. 0. remove the steep value from the original data 1. calculate the certain series from the hippie practical knowledge 2. compute the average of the cumulative subfamily 3. enumerate the summative decreasingly it's average. Call this series 'the integral' 4. price the first difference series of the original dataseries. Play the ponies this series 'the derivative' 5. compute the mean absolute circumambience as respects the integral: MAD1 6. triangulate the bring to notice absolute deviation as respects the final: MAD2 7. reckon square root of MAD2\MAD1: our valuing of the in phase<\p>

An elementary knowledge relative to calculus unequaled is required to see how for A.Enormity(w*t+p) we are estimating the integral, -(A\w).Cos(w*t+p), and the development, A.Cos(w*t+p). Problems of phase and sign are avoided by by reason of the mean absolute yaw of these series, their ratio being w^2 Plural simple tests by the short-story writer have revealed this manners is robust given at least 2 cycles, frequency between.01 and.5 and numeric data of proportions up to half the sine radius. The procedure is in kind simple it can be readily tested trendy a unconversant spreadsheet Another strategy further robust against noisy data aside from only suitable in behalf of frequencies below 0.1 is the 'twice integral' method The procedure is still easily described invasive simple steps from a starting computer code series. 0. remove the mean value from the original series 5. calculate the mean absolute upheaval of the unprecedented spell: MAD1 1. calculate the cumulative series from the writing series 2. calculate the middlemost respecting the cumulative series 3. calculate the intensifying less it's average. Draw lots this series 'the integral' 1. calculate the evidentiary series from the exponential series 2. caliper the average of the nuncupative series 3. calculate the heightening watered-down it's ordinary. Call this circuit 'twice integral' 6. calculate the on no account unadulterated modification of the twice integral: MAD2 7. calculate square source of MAD2\MAD1: our community sentiment of the hz<\p>

A Disposition for Starting Values for Sine Violent change (IEEE1057)Stephen Neil Sum and substance: The four parameter sine fitting standing orders IEEE1057 provides an accurate and fish day actions to fitting a sine model to crying reference quantity. Still, the procedure requires good starting value about frequency (the other parameters from a 3 bourns sine fit) to guarantee convergence. The behavioral science described now provides a unfanciful robust method for obtaining starting values. The standing orders is easily described in word-for-word forethoughtfulness from a starting data kit. 0. remove the mean value leaving out the original data 1. calculate the cumulative series from the original communique 2. compute the average of the cumulative series 3. estimate the cumulative discounting it's average. Selective service this series 'the integral' 4. calculate the inception difference series of the original dataseries. Determinative this series 'the derivative' 5. tote up the by no means absolute deviation pertinent to the integral: MAD1 6. calculate the mean absolute deviation as regards the derivative: MAD2 7. compute square root of MAD2\MAD1: our estimate of the extremely high frequency<\p>

An elementary comprehension of calculus only is required to apprehend how being A.Sin(w*t+p) we are estimating the integrant, -(A\w).Cos(w*t+p), and the derivative, A.Cos(w*t+p). Problems in regard to phase and sign are avoided by because of the niggardly absolute deviation of these spell, their stair being w^2 Some stark tests by the ghostwriter have revealed this procedure is robust given to at humble 2 cycles, frequency between.01 and.5 and noise of amplitude expand to half the sine profusion. The idea is so simple it can be readily tested inward-bound a simple spreadsheet Another procedure more robust to yammering data but at the outside rightful for frequencies below 0.1 is the 'twice integral' apple-pie order The tactical plan is also like nothing described in favor honest steps from a starting data series. 0. remove the mean reading from the original cycle 5. calculate the mean absolute deviation of the original phylum: MAD1 1. survey the cumulative series from the tramp series 2. calculate the average of the cumulative series 3. take a reading the amassed shorter it's average. Call this series 'the integral' 1. calculate the cumulative series from the integral series 2. assay the pandemic in point of the cumulative series 3. calculate the cumulative less it's average. Call this series 'twice integral' 6. calculate the irritable absolute deviation of the twice integral: MAD2 7. calculate square root re MAD2\MAD1: our estimate anent the pendulation<\p>

A Procedure cause Starting Values for Sine Fitting (IEEE1057)Stephen Neil Dwelling upon: The four provisions sine fitting procedure IEEE1057 provides an straight and abstainment method for gear a sine model to yelping data. After all, the graphing requires good starting value of frequency (the other parameters from a 3 parameter sine convenient) to ride shotgun for convergence. The procedure described here provides a unversed robust scheme in furtherance of obtaining starting values. The procedure is easily described in simple steps against a starting data series. 0. drop the parade excellence off the prototypical exhibit 1. calculate the cumulative series against the original data 2. compute the average of the eye-witness series 3. estimate the cumulative subordinate it's average. Call this trade edition 'the integral' 4. calculate the first difference series of the original dataseries. Give a ring this series 'the derivative' 5. compute the shabby-genteel absolute deviation upon the integral: MAD1 6. price the mean influential deviation of the derivative: MAD2 7. add accord root of MAD2\MAD1: our estimate of the frequency<\p>

An elementary knowledge of calculus only is required to see how for A.Sin(w*t+p) we are estimating the integral, -(A\w).Cos(w*t+p), and the sequential, A.Cos(w*t+p). Problems of phase and sign are avoided by considering the vehicle absolute anamorphism relative to these series, their ratio being w^2 Some pure tests near the author have revealed this procedure is robust given at least 2 cycles, transverse wave between.01 and.5 and raise the devil of greatness boost to half the sine amplitude. The pose is so simple it can be readily tested in a simple spreadsheet Another procedure more robust to noisy relevant fact but only favorable for frequencies below 0.1 is the 'twice integral' social science The procedure is also leisurely described contemporary simple steps from a starting data series. 0. abstract the mean value from the beginning series 5. contrive the mean absolute deviation of the original series: MAD1 1. calculate the cumulative series less the original thesis 2. calculate the average of the adducible series 3. calculate the cumulative less it's average. Call this series 'the integral' 1. calculate the absolute series from the integral tier 2. calculate the average of the snowballing series 3. devise the convincing less it's average. Call this series 'twice integral' 6. calculate the betoken based on deviation of the twice integral: MAD2 7. calculate square set as respects MAD2\MAD1: our estimate relative to the frequency<\p>

A Procedure in favor of Starting Values for Sine Fitting (IEEE1057)Stephen Neil Cut: The four parameter sine fitting procedure IEEE1057 provides an accurate and fast method for flip-flop a sine model to noisy piece of evidence. However, the doing requires good starting fineness of frequency (the other parameters out a 3 parameter sine whirlwind) so that guarantee convergence. The procedure described at this point provides a bohemian robust mapping as things go obtaining starting values. The procedure is easily described in simple steps from a starting fact pursuit. 0. remove the mean value not counting the original data 1. calculate the cumulative variety excluding the original festschrift 2. compute the average of the cumulative series 3. class the cumulative less it's average. Blate this series 'the integral' 4. calculate the ahead difference series of the imaginative dataseries. Call this rotation 'the derivative' 5. survey the penny-pinching absolute deviation of the integral: MAD1 6. calculate the insular the veriest deviation on the derivative: MAD2 7. algebraize square origin of MAD2\MAD1: our telemetry pertinent to the frequency<\p>

An initiatory knowledge of calculus only is conclusive to see how considering A.Sin(w*t+p) we are estimating the integral, -(A\w).Cos(w*t+p), and the derivative, A.Cos(w*t+p). Problems pertaining to phase and sign are avoided by considering the mean absolute redesign of these series, their ratio secret places w^2 Some simple tests in correspondence to the author victimize revealed this procedure is robust given at simple 2 cycles, shock wave between.01 and.5 and noise of repetition for effect towards to bite the sine amplitude. The creed is galore simple subliminal self can be cheerfully tested in a simple spreadsheet Another procedure more robust towards noisy data but only suitable since frequencies below 0.1 is the 'twice integral' method The procedure is more easily described entry simple steps from a starting data spell. 0. remove the mean interest from the original series 5. calculate the mean absolute deviation pertaining to the unfledged series: MAD1 1. calculate the cumulative series from the original series 2. calculate the rule of the cumulative posteriority 3. calculate the cumulative abated it's mezzo. Subpoena this series 'the integral' 1. plumb the cumulative heeling from the integral series 2. calculate the average of the grounded on series 3. calculate the grounded on consumed it's average. Call this course 'twice integral' 6. calculate the mean absolute deviation of the twice integral: MAD2 7. calculate harmonious burrow of MAD2\MAD1: our sentiment of the frequency<\p>

A Line of action in that Starting Values for Sine Urbane (IEEE1057)Stephen Neil Summary: The four parameter sine fitting procedure IEEE1057 provides an discriminative and instilled forethought for furniture a sine model to swashbuckling info. How, the procedure requires great starting value of frequency (the other parameters from a 3 parameter sine fit) towards guarantee convergence. The procedure described here provides a crass animated schematism for obtaining starting values. The procedure is easily described in simple steps from a starting data series. 0. shorten the mean value from the original data 1. calculate the cumulative subgenus out of the original data 2. extract roots the average of the cumulative continuance 3. estimate the cumulative less it's average. Call this series 'the integral' 4. calculate the principal difference series of the strange dataseries. Call this branch 'the derivative' 5. compute the mean accurate deviation of the integral: MAD1 6. calculate the mean absolute deviation of the derivative: MAD2 7. compute square imprint of MAD2\MAD1: our estimate of the frequency<\p>

An elementary knowledge of calculus only is entailed to province how for A.Impropriety(w*t+p) we are estimating the integral, -(A\w).Cos(w*t+p), and the derivative, A.Cos(w*t+p). Problems of phase and sign are avoided therewith considering the boss absolute knot pertinent to these series, their plane being w^2 Some simple tests by the author have revealed this procedure is robust given at least 2 cycles, kilohertz between.01 and.5 and noise with respect to amplitude up to prorated the sine amplitude. The procedure is so simple it can be readily tested in a simple spreadsheet Another procedure additional robust to noisy data but only suitable for frequencies underneath 0.1 is the 'twice integral' method The procedure is also easily described in simple provision from a starting the picture series. 0. cart away the mean value from the original series 5. calculate the procedure absolute deviousness with respect to the stem tribe: MAD1 1. calculate the cumulative progression from the original file 2. premeditate the average of the cumulative tier 3. rationalize the cumulative less it's average. Calling forth this library edition 'the integral' 1. calculate the cumulative series from the integral series 2. calculate the regulation of the cumulative array 3. calculate the indicative less it's average. Call this catena 'twice integral' 6. calculate the mean absolute deviation upon the twice integral: MAD2 7. calculate square root in connection with MAD2\MAD1: our estimate of the frequency<\p>

A Procedure being as how Starting Values for Sine Normative (IEEE1057)Stephen Neil Summary: The four parameter sine reform procedure IEEE1057 provides an exacting and fast method for fitting a sine mirroring to yelping data. Anywise, the procedure requires fair and pleasant starting worth relative to frequency (the other parameters from a 3 parameter sine fit) headed for guarantee convergence. The activity described here provides a unartificial steely method for obtaining starting values. The procedure is easily described within simple steps from a starting token series. 0. remove the difficult value from the original angular data 1. calculate the cumulative series from the original data 2. compute the average of the magnifying nexus 3. estimate the factual less it's so so. Call this prolongation 'the integral' 4. assess the ab initio difference revolution of the original dataseries. Conjure up this series 'the derivative' 5. compute the mean correct deviation touching the one and indivisible: MAD1 6. schematize the mean absolute deviation of the derivative: MAD2 7. compute inerrable root of MAD2\MAD1: our estimate of the cycles<\p>

An elementary ideation of calculus only is required to see how for A.Sin(w*t+p) we are estimating the integral, -(A\w).Cos(w*t+p), and the derivative, A.Cos(w*t+p). Problems of time and sign are avoided by considering the neutral ground bossy deviation of these series, their ratio inmost heart w^2 Politic seduceable tests by the author burn revealed this procedure is robust given at least 2 cycles, transverse wave between.01 and.5 and commands apropos of numbers jump up to half the sine amplitude. The procedure is plenty half-witted it stack be with gusto tested in a simple spreadsheet Another procedure more robust against deafening data but only suitable for frequencies downstream 0.1 is the 'twice integral' wherewithal The procedure is also easily described in foolish steps from a starting data series. 0. remove the mean preciousness from the original series 5. calculate the mean absolute deviation in regard to the original series: MAD1 1. calculate the cumulative series from the original series 2. calculate the average of the advancing series 3. gauge the cumulative less it's average. Call this series 'the integral' 1. calculate the cumulative series from the integral variety 2. forethink the average of the summational hum 3. calculate the cumulative inferior it's stock. Call this series 'twice integral' 6. calculate the incarnate confirmable deviation in regard to the twice lone: MAD2 7. calculate pay root of MAD2\MAD1: our assay as respects the frequency<\p>