Let S be a set of 2n points on a circle such that for each point p 2 S also its antipodal (mirrored with respect to the circle center) point p 0 belongs to S. A polygon P of size n is called antipodal if it consists of precisely one point of each antipodal pair (p;p 0 ) of S. We provide a complete characterization of antipodal polygons which maximize (minimize, respectively) the area among all antipodal polygons ofS. Based on this characterization, a simple linear time algorithm is presented for computing extremal antipodal polygons. Moreover, for the generalization of antipodal polygons to higher dimensions we show that a similar characterization does not exist.
In our case, an antipodal polygon is related with the concept in music theory. Typically, the notes of a scale are represented by a polygon in a clock diagram. In a chromatic scale, each whole tone can be further divided into two semitones. Thus, we can think in a clock diagram with twelve points representing the twelve equally spaced pitches that represent the chromatic universe (using an equal tempered tuning). The pitch class diagram is illustrated in Figure . A tritone is traditionally defined as a musical interval composed of three whole tones. Thus, it is any interval spanning six semitones. In Figure a), the polygon represents a scale containing the tritones @math . The tritone is defined as a restless interval or dissonance in Western music from the early Middle Ages. This interval was frequently avoided in medieval ecclesiastical singing because of its dissonant quality. The name (the Devil in music) has been applied to the interval from at least the early 18th century @cite_6 .
@cite_6
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The cognitive representation of harmonic and tonal structure in Western music is investigated using a tone-profile technique. In this method listeners rate how well single tones (any one of the 12 tones of the chromatic scale) follow a musical element such as a scale, chord, or cadence. Very stable rating profiles reflecting the tonal hierarchies in major and minor keys are obtained, which, when intercorrelated and analyzed using multidimensional scaling, produce a four-dimensional spatial map of the distances between keys. The keys are located on the surface of a torus, in which the circle of fifths and the parallel and relative relations between major and minor keys are represented. In addition, single chords (major, minor, diminished, and dominant seventh) are found to be closely associated with the major and minor keys in which they play harmonic functions. The developing and changing sense of key during sequences of chords is traced by obtaining probe tone ratings following each chord in 10 different sequences, 8 of which contain modulations (changes) between keys. Modulations between closely related keys are found to be effected more immediately than are modulations between relatively distant keys. In all cases beyond the initial chord, the sense of the prevailing key is stronger than that produced by the last heard chord in isolation. Thus, listeners integrate harmonic functions over multiple chords, developing a sense of key that may need to be reevaluated as additional chords are sounded. It is suggested that the perceived relations between chords and keys and between different keys are mediated through an internal representation of the hierarchy of tonal functions of single tones in music. Music consists of tones varying in pitch, serve to highlight rhythmic patterns, further duration, loudness, and timbre, but the per- emphasize phrase structure, and distinguish ception of music extends well beyond the between tones constituting the primary meregistration of these physical attributes of lodic line and tones serving more ornamental the musical stimulus. Indeed, music contains or harmonic functions. Timbral characterconsiderable structure even in the relations istics may additionally provide important that obtain among the individual tones. For cues for the overall structure of the musical example, the durations are such that metri- composition. A musical scale can be viewed as a subset of notes or pitches taken from a chromatic universe. For the purposes of this paper we consider a chromatic universe of twelve equally spaced pitches. Given integers (N,K) with N > K we use particular integer partitions of N into K parts to construct distinguished sets, or scales. We show that a natural geometric realization of these sets have maximal area, so we call them maximal area sets. We then discuss properties of maximal area sets for the integer pairs (12,5) (12,6) (12,7) and (12,8) with the obvious relevance to scales in our normal chromatic collection of 12 pitches. Complementary maximal area sets are those sets where the chosen K notes realize maximal area, and the complementary N − K notes also realize maximal area. The complementary maximal area sets closely match a significant collection of scales identified in a book on jazz theory by Mark Levine(The jazz theory book. Sher Music Co., Pet aluma, 1995). Temporal pitch class profiles - commonly referred to as a chromagrams - are the de facto standard signal representation for content-based methods of musical harmonic analysis, despite exhibiting a set of practical difficulties. Here, we present a novel, data-driven approach to learning a robust function that projects audio data into Tonnetz-space, a geometric representation of equal-tempered pitch intervals grounded in music theory. We apply this representation to automatic chord recognition and show that our approach out-performs the classification accuracy of previous chroma representations, while providing a mid-level feature space that circumvents challenges inherent to chroma. We examined a variety of real-time responses evoked by a single piece of music, the organ Duetto BWV 805 by J S Bach. The primary data came from a concurrent probe-tone method in which the probe tone is sounded continuously with the music. Listeners judged how well the probe tone fit with the music at each point in time. The process was repeated for all probe tones of the chromatic scale. A self-organizing map (SOM) (Kohonen 1997 Self-organizing Maps (Berlin: Springer)) was used to represent the developing and changing sense of key reflected in these judgments. The SOM was trained on the probe-tone profiles for 24 major and minor keys (Krumhansl and Kessler 1982 Psychological Review 89 334^368). Projecting the concurrent probe-tone data onto the map showed changes both in the perceived keys and in their strengths. Two dynamic models of tonality induction were tested. Model 1 is based on pitch class distribu- tions. Model 2 is based on the tone-transition distributions; it tested the idea that the order of tones might provide additional information about tonality. Both models contained dynamic components for characterizing pitch strength and creating pitch memory representations. Both models produced results closely matching those of the concurrent probe-tone data. Finally real- time judgments of tension were measured. Tension correlated with distance away from the predominant key in the direction of keys built on the dominant and supertonic tones, and also correlated with dissonance.