Tp tuning: Difference between revisions

Wikispaces>genewardsmith
**Imported revision 348181842 - Original comment: **
Wikispaces>genewardsmith
**Imported revision 348184558 - Original comment: **
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<h2>IMPORTED REVISION FROM WIKISPACES</h2>
<h2>IMPORTED REVISION FROM WIKISPACES</h2>
This is an imported revision from Wikispaces. The revision metadata is included below for reference:<br>
This is an imported revision from Wikispaces. The revision metadata is included below for reference:<br>
: This revision was by author [[User:genewardsmith|genewardsmith]] and made on <tt>2012-06-26 14:01:37 UTC</tt>.<br>
: This revision was by author [[User:genewardsmith|genewardsmith]] and made on <tt>2012-06-26 14:08:05 UTC</tt>.<br>
: The original revision id was <tt>348181842</tt>.<br>
: The original revision id was <tt>348184558</tt>.<br>
: The revision comment was: <tt></tt><br>
: The revision comment was: <tt></tt><br>
The revision contents are below, presented both in the original Wikispaces Wikitext format, and in HTML exactly as Wikispaces rendered it.<br>
The revision contents are below, presented both in the original Wikispaces Wikitext format, and in HTML exactly as Wikispaces rendered it.<br>
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# Convert the monzos to weighted coordinates.
# Convert the monzos to weighted coordinates.
# Multiply each monzo by an indeterminate, creating a parametrized n-dimensional weighted monzo, where n is the number of primes in the prime limit; call that M.
# Multiply each monzo by an indeterminate, creating a parametrized n-dimensional weighted monzo, where n is the number of primes in the prime limit; call that M.
# Take the dot product of M with a vector consisting of n new indeterminates x1, x2, ..., xn, and take the dot product of that with M; call that X.
# Take the dot product of M with a vector &lt;x1 x2 ... xn| consisting of n new indeterminates x1, x2, ..., xn; call that X.
# Maximize X^2 subject to the constraint that the M.M, the dot product of M with itself, is equal to 1. This is maximinzing a quadric subject to a quadratic constraint, and so this is easily done via Lagrange multipliers.
# Maximize X^2 subject to the constraint that the M.M, the dot product of M with itself, is equal to 1. This is maximinzing a quadric subject to a quadratic constraint, and so is easily done via Lagrange multipliers.
# The result of the maximization process is a positive definite quadratic form Q(x1, x2, ..., xn) in n indeterminates x1, x2, ..., xn.
# The result of the maximization process is a positive definite quadratic form Q(x1, x2, ..., xn) in n indeterminates x1, x2, ..., xn.
# Find the point T on the subspace of G-tuning space spanned by the [[Gencom|gencom mapping]] closest to the JIP, which as usual is &lt;1 1 1 ... 1|.
# Find the point T on the subspace of G-tuning space spanned by the [[Gencom|gencom mapping]] closest to the JIP using the distance function defined by Q. As usual the JIP is &lt;1 1 1 ... 1|. Since Q is a quadratic polynomial, this minimal distance is easily found by calculus methods.
# Since the primes may or may not be in the group G, the mapping of primes in T may or may not make sense by itself; however, now unweight T and apply it to the generators of the gencom, and obtain the TE tuning of those generators, which defines the TE tuning for the temperament defined by the gencom.</pre></div>
# Since the primes may or may not be in the group G, the mapping of primes in T may or may not make sense by itself; however, now unweight T and apply it to the generators of the gencom, and obtain the TE tuning of those generators, which defines the TE tuning for the temperament defined by the gencom.</pre></div>
<h4>Original HTML content:</h4>
<h4>Original HTML content:</h4>
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In the special case where p = 2, the Lp norm becomes the L2 norm, which is the &lt;a class="wiki_link" href="/Tenney-Euclidean%20metrics"&gt;Tenney-Euclidean&lt;/a&gt; norm, or TE complexity. Associated to this norm is L2 tuning, or TE tuning, extended to arbitrary JI groups. Starting from a &lt;a class="wiki_link" href="/gencom"&gt;gencom&lt;/a&gt; for the temperament, we may find the tuning by the following proceedure:&lt;br /&gt;
In the special case where p = 2, the Lp norm becomes the L2 norm, which is the &lt;a class="wiki_link" href="/Tenney-Euclidean%20metrics"&gt;Tenney-Euclidean&lt;/a&gt; norm, or TE complexity. Associated to this norm is L2 tuning, or TE tuning, extended to arbitrary JI groups. Starting from a &lt;a class="wiki_link" href="/gencom"&gt;gencom&lt;/a&gt; for the temperament, we may find the tuning by the following proceedure:&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;ol&gt;&lt;li&gt;Convert the gencom into monzo form.&lt;/li&gt;&lt;li&gt;Convert the monzos to weighted coordinates.&lt;/li&gt;&lt;li&gt;Multiply each monzo by an indeterminate, creating a parametrized n-dimensional weighted monzo, where n is the number of primes in the prime limit; call that M.&lt;/li&gt;&lt;li&gt;Take the dot product of M with a vector consisting of n new indeterminates x1, x2, ..., xn, and take the dot product of that with M; call that X.&lt;/li&gt;&lt;li&gt;Maximize X^2 subject to the constraint that the M.M, the dot product of M with itself, is equal to 1. This is maximinzing a quadric subject to a quadratic constraint, and so this is easily done via Lagrange multipliers.&lt;/li&gt;&lt;li&gt;The result of the maximization process is a positive definite quadratic form Q(x1, x2, ..., xn) in n indeterminates x1, x2, ..., xn.&lt;/li&gt;&lt;li&gt;Find the point T on the subspace of G-tuning space spanned by the &lt;a class="wiki_link" href="/Gencom"&gt;gencom mapping&lt;/a&gt; closest to the JIP, which as usual is &amp;lt;1 1 1 ... 1|.&lt;/li&gt;&lt;li&gt;Since the primes may or may not be in the group G, the mapping of primes in T may or may not make sense by itself; however, now unweight T and apply it to the generators of the gencom, and obtain the TE tuning of those generators, which defines the TE tuning for the temperament defined by the gencom.&lt;/li&gt;&lt;/ol&gt;&lt;/body&gt;&lt;/html&gt;</pre></div>
&lt;ol&gt;&lt;li&gt;Convert the gencom into monzo form.&lt;/li&gt;&lt;li&gt;Convert the monzos to weighted coordinates.&lt;/li&gt;&lt;li&gt;Multiply each monzo by an indeterminate, creating a parametrized n-dimensional weighted monzo, where n is the number of primes in the prime limit; call that M.&lt;/li&gt;&lt;li&gt;Take the dot product of M with a vector &amp;lt;x1 x2 ... xn| consisting of n new indeterminates x1, x2, ..., xn; call that X.&lt;/li&gt;&lt;li&gt;Maximize X^2 subject to the constraint that the M.M, the dot product of M with itself, is equal to 1. This is maximinzing a quadric subject to a quadratic constraint, and so is easily done via Lagrange multipliers.&lt;/li&gt;&lt;li&gt;The result of the maximization process is a positive definite quadratic form Q(x1, x2, ..., xn) in n indeterminates x1, x2, ..., xn.&lt;/li&gt;&lt;li&gt;Find the point T on the subspace of G-tuning space spanned by the &lt;a class="wiki_link" href="/Gencom"&gt;gencom mapping&lt;/a&gt; closest to the JIP using the distance function defined by Q. As usual the JIP is &amp;lt;1 1 1 ... 1|. Since Q is a quadratic polynomial, this minimal distance is easily found by calculus methods.&lt;/li&gt;&lt;li&gt;Since the primes may or may not be in the group G, the mapping of primes in T may or may not make sense by itself; however, now unweight T and apply it to the generators of the gencom, and obtain the TE tuning of those generators, which defines the TE tuning for the temperament defined by the gencom.&lt;/li&gt;&lt;/ol&gt;&lt;/body&gt;&lt;/html&gt;</pre></div>