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<blockquote data-quote="Michael John" data-source="post: 147863" data-attributes="member: 830"><p>Re: FIR filters</p><p></p><p></p><p></p><p>Thanks very much Frank. My apologies in advance for taking some time to think over this.</p><p></p><p>To your earlier post. You mentioned averaging the log-magnitude of multiple measurements, without respect to time alignment, to make a good magnitude response, and then make a minimum phase FIR. That makes sense. I've vaguely recall reading about the pro's and con's between averaging log-magnitude versus averaging the IR signal directly. Something about the log average being more influenced by level outliers. Without more thought, I don't have an opinion here but I thought it's worth mentioning.</p><p></p><p>The Auto Mag tab on my app creates a minimum-phase FIR. (I might add a linear phase option.) Your step to combine this filter minimum-phase with a FIR all-pass sounds very similar to the manual Phase Adjust on my app. I apply the manual Phase Adjust first, so the Auto Mag and Auto Phase processes don't have to fight with the excessive phase. I guess you're doing this too.</p><p></p><p>A few weeks ago I discovered that the complex averaging in the frequency smoothing in the Auto Mag process was loosing energy when there was excessive phase rotation in the response. To prevent this, I added the option for magnitude-only frequency smoothing. This helps a lot for some messy measurements, or for filters where the manual Phase Adjust page has high phase rotation added. Why one would extra phase slope, I don't know, since the intent is to make phase smoother!</p><p></p><p>In the context of high frequency corrections, such as fixing horn resonances, I suspect that direct IR averaging is necessary and possibly with oversampling to get the most accurate time alignment possible. Steve Anderson and I were just yesterday discussing this, and I can easily write a tool that, for example, reads all the IR's in a directory, does oversampling, time (and maybe level) alignment, and spits out the average response. If the files are annotated with direction, it could apply some directional weighting, or other heuristics. I could maybe add multiple-measurement averaging as an import option in the FIR tool.</p></blockquote><p></p>
[QUOTE="Michael John, post: 147863, member: 830"] Re: FIR filters Thanks very much Frank. My apologies in advance for taking some time to think over this. To your earlier post. You mentioned averaging the log-magnitude of multiple measurements, without respect to time alignment, to make a good magnitude response, and then make a minimum phase FIR. That makes sense. I've vaguely recall reading about the pro's and con's between averaging log-magnitude versus averaging the IR signal directly. Something about the log average being more influenced by level outliers. Without more thought, I don't have an opinion here but I thought it's worth mentioning. The Auto Mag tab on my app creates a minimum-phase FIR. (I might add a linear phase option.) Your step to combine this filter minimum-phase with a FIR all-pass sounds very similar to the manual Phase Adjust on my app. I apply the manual Phase Adjust first, so the Auto Mag and Auto Phase processes don't have to fight with the excessive phase. I guess you're doing this too. A few weeks ago I discovered that the complex averaging in the frequency smoothing in the Auto Mag process was loosing energy when there was excessive phase rotation in the response. To prevent this, I added the option for magnitude-only frequency smoothing. This helps a lot for some messy measurements, or for filters where the manual Phase Adjust page has high phase rotation added. Why one would extra phase slope, I don't know, since the intent is to make phase smoother! In the context of high frequency corrections, such as fixing horn resonances, I suspect that direct IR averaging is necessary and possibly with oversampling to get the most accurate time alignment possible. Steve Anderson and I were just yesterday discussing this, and I can easily write a tool that, for example, reads all the IR's in a directory, does oversampling, time (and maybe level) alignment, and spits out the average response. If the files are annotated with direction, it could apply some directional weighting, or other heuristics. I could maybe add multiple-measurement averaging as an import option in the FIR tool. [/QUOTE]
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