Diffusion-based molecular communication system (DBMC) is a system in which information-carrying molecules are sent from the transmitter and passively transported to the receiver in a fluid environment. Nanomachines, which are the main part of this system, have limited processing capacity. Besides, at the receiver, high inter-symbol interference (ISI) occurs due to free movement of molecules and the variance of the observation noise is signal dependent. Hence, it is important to design high-performance and low complexity receiver detection methods. In this paper, finite impulse response (FIR) Wiener filter is introduced for the first time, which has considerably less computational complexity compared to the minimum mean square error (MMSE) algorithm proposed in the literature. Moreover, extended Kalman filter is introduced for the first time to DBMC as a receiver detection method. Finally, Viterbi algorithm is modified and used as a benchmark for performance evaluation.