With increasing electrical energy demand and loading of transmission lines, inter-area oscillations within a frequency range of 0.2 to 0.8 Hz are more obvious in modern power systems which are the most important reason for oscillatory rotor angle instability. When inter-area modes are excited, the power system is divided into areas in which generators at each area are coherent but they are anti-phase oscillation respect to other generator groups. The interarea oscillations have a lower frequency and damping ratio than local modes, and they cause power oscillation at tie-lines between areas that restricts the power transmission capacity. Therefore, online monitoring and control of inter-area modes are vital for secure and reliable operation of the power system. With the recent advancement of the technology and the emergence of wide area measurement systems (WAMSs) and the possibility of measure phasor quantities using phasor measurement units (PMUs), the dynamic response of power system can be online monitored using data analysis and signal processing techniques. The main feature of signal processing techniques is that they don’t need any knowledge about the power system order or power equipment models. In this thesis, a hybrid method based on WAMS for the detection of dominant inter-area oscillation modes and evaluation of generators oscillation patterns at each considerable mode is proposed. The proposed method can also detect the most efficient damping controller loops for improving the damping of dominant oscillation modes. The proposed method uses the empirical mode decomposition (EMD) algorithm and correlation analysis (CA) technique. In the first step, the frequency components of measured signals are decomposed from highest to lowest frequency by the EMD algorithm and then, the instantaneous frequency characteristics of each extracted component are calculated by hilbert huang transform (HHT). Power system oscillation modes are identified by comparing the frequency averages with the typical frequency range of low-frequency electromechanical oscillations (LFEOs), and finally, the dominant oscillation modes are determined by comparing the instantaneous energy level of oscillation modes. One feature of the EMD algorithm is the ability to extract waveforms of oscillation modes. Considering dominant mode waveforms as the input for correlation analysis, it can determine how generators oscillate against each other by calculating the phase difference between signals. Furthermore, efficient feedback signals can be determined by estimation relative magnitude of mode shape or right eigenvectors. Moreover, by comparing left eigenvectors magnitudes, efficient damping controllers can be specified. In other words, the efficient damping controller loops based on observability and controllability concepts related to right and left eigenvectors can be identified. The applicability of the proposed method in this thesis is demonstrated by several analyses and simulations on IEEE-9 bus and IEEE-39 bus test systems. Keywords Inter-Area Oscillations, Phasor Measurement Unit (PMU), Empirical Mode Decomposition (EMD) Algorithm, Correlation Analysis (CA), Mode Shape, Wide Area Damping Controller (WADC)