不管是多個相同的樂器或不同樂器，當同時演奏的音符有倍頻重疊的部分，在音樂訊號處理上，音符的分離就變得比較的困難。為了要去處理這樣的問題，就必須要將個別樂器聲音中單一不變的特性加入分離的程序當中協助分析。譬如說，音色就是一個可以被用來當作代表各個樂器聲音可能不會變動的特性。
在這篇論文章中，音色的估測結果被用來代表這樣的特性，用來當作協助分析的限制，被執行在比較複雜的音樂訊號分離當中。為了去實行這個方法，我將這個方法用於取決於時間的遞迴迴歸分析(time-dependent recursive regularization analysis, TD-RR). 將各個不同的音符訊號的頻譜包絡估測出來並在遞迴迴歸中調整其中更新的參數
這個實驗的結果會顯示出因為被頻重疊的問題所造成的缺漏能夠透過這樣的方法被有效的減少。

Note separation in music signal processing becomes difficult when there are overlapping partials of co-existing notes produced by either the same or different musical instruments. In order to deal with this problem, it is necessary to involve certain invariant features of musical instrument sounds into the separation processing. For example, the timbre of a note of a musical instrument may be used as one possible invariant feature.
In this thesis a timbre estimate is used to represent this feature such that it becomes a constraint when the note separation is performed on a mixture signal. To demonstrate the proposed method, a time-dependent recursive regularization analysis is employed. Spectral envelopes of different notes are estimated and a modified parameter update strategy is applied to the recursive regularization process.
The experimental results show that the flaws due to the overlapping partial problem can be effectively reduced through the proposed approach.

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