author = "Ferreira, Maria Teodora and Fmann, Rosangela and Macau, Elbert E. 
                         N. and Domingues, Margarete O.",
          affiliation = "{} and {} and {Instituto Nacional de Pesquisas Espaciais (INPE)} 
                         and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Detecting phase synchronization in coupled chaotic noncoherent 
                         oscillators by using complexwavelet transform",
            booktitle = "Proceedings...",
                 year = "2013",
               editor = "et. al. , Z. Dimitrovov' a",
         organization = "International Conference on Vibration Problems, 11. (ICOVP).",
             keywords = "chaos, phase synchronization, synchronization in chaotic systems, 
                         wavelet, dynamical.",
             abstract = "Phase synchronization in nonidentical coupled chaotic systems 
                         appears for some conditions in which weak coupling causes the 
                         systems evolution on time to lock in phase to one another, while 
                         their amplitudes may remain chaotic and are, in general, 
                         uncorrelated. To identify this phenomenon, given a signal it is 
                         necessary to measure properly its phase. If a system has a 
                         dominant peak in the power spectrum, there are several methods to 
                         define the phase. However, if the signal has a broad-band 
                         spectrum, which is typical for non-coherent signal, then the 
                         measurement of the phase may be a challenge. Phase is defined as 
                         an increasing function of time. The standard method for measuring 
                         phase does no complain with this requirement. In this work we 
                         present an innovative method for measuring phase that complain 
                         with the increasing function of time requirement. This method is 
                         based on Dual Tree Complex Wavelet Transform, which is a form of 
                         discrete wavelet transform that generates complex coefficient by 
                         using a dual tree wavelet filters to obtain their real and 
                         imaginary parts. The proposed approach is robust and 
                         computationally efficient. Furthermore, this approach shows 
                         flexibility and in principle is applicable to any experimental 
                         time serie.",
  conference-location = "Lisbon",
      conference-year = "912 Sep. 2013",
             language = "en",
           targetfile = "mteodoraf_ICOVP2013.pdf",
        urlaccessdate = "16 jan. 2021"