From PICLIST@MITVMA.MIT.EDU Fri Nov 15 13:30:50 2002 Received: from cherry.ease.lsoft.com [209.119.0.109] by dpmail10.doteasy.com with ESMTP (SMTPD32-7.13) id A78A1C8D00CA; Fri, 15 Nov 2002 13:30:50 -0800 Received: from PEAR.EASE.LSOFT.COM (209.119.0.19) by cherry.ease.lsoft.com (LSMTP for Digital Unix v1.1b) with SMTP id <7.007DD959@cherry.ease.lsoft.com>; Fri, 15 Nov 2002 16:16:36 -0500 Received: from MITVMA.MIT.EDU by MITVMA.MIT.EDU (LISTSERV-TCP/IP release 1.8d) with spool id 8750 for PICLIST@MITVMA.MIT.EDU; Fri, 15 Nov 2002 15:54:55 -0500 Received: from MITVMA (NJE origin SMTP@MITVMA) by MITVMA.MIT.EDU (LMail V1.2d/1.8d) with BSMTP id 0342; Fri, 15 Nov 2002 15:54:12 -0500 Received: from *unknown [65.112.57.227] by mitvma.mit.edu (IBM VM SMTP Level 320) via TCP with ESMTP ; Fri, 15 Nov 2002 15:54:11 EST X-Warning: mitvma.mit.edu: Host *unknown claimed to be webmail.saltonusa.com MIME-Version: 1.0 X-Mailer: Lotus Notes Release 5.0.10 March 22, 2002 X-MIMETrack: Serialize by Router on NOTES/SALTON(Release 5.0.10 |March 22, 2002) at 11/15/2002 02:54:50 PM, Serialize complete at 11/15/2002 02:54:50 PM Content-Type: text/plain; charset="us-ascii" Message-ID: Date: Fri, 15 Nov 2002 14:54:38 -0600 Reply-To: pic microcontroller discussion list Sender: pic microcontroller discussion list From: llile@SALTONUSA.COM Subject: Re: [EE]:Pressure sensor confusion Comments: To: Gordon Williams To: PICLIST@MITVMA.MIT.EDU X-RCPT-TO: Status: R X-UIDL: 277600737 X-Evolution-Source: pop://mailinglist%40farcite.net@mail.farcite.net/ X-Evolution: 000007a6-0000 That's one way to deal with it. A typical problem for me is interpolating thermistor data. The thermistor curve comes in chart form from the manufacturer, in very un-handy increments. It's quite a complex curve, and I think curve fitting it would be a long involved task (unless Excel does this automatically somehow? ) Linear curve fitting would be a cinch. The only way I know how to curve fit a nonlinear is, guess at the type of equation to use, plot it next to your data, sum the squares of the differences, then run a linear regression on the results and use a Tools:GoalSeek on the results to approach the minimum, then guess again at the type of equation to use until you like the fit.. It is a time-consuming process, usually. Is there a more efficient way? -- Lawrence Lile "Gordon Williams" 11/15/02 01:21 PM To: cc: Subject: Re: Re: [EE]:Pressure sensor confusion The way that I usually handle it is to plot the experimental data, put my choice of curve fit on the graph and have it show the equation for the curve. The equation then can be used for interpolation or extrapolation. Gordon Williams -- http://www.piclist.com hint: The PICList is archived three different ways. See http://www.piclist.com/#archives for details.