This paper presents several signal processing approaches in Trojan detection problem in very large scale integrated circuits. Specifically, wavelet transforms, spectrograms and neural networks are used to analyze power side-channel signals. Trojans in integrated circuits can try to hide themselves and become almost invisible due to process and measurement noises. We demonstrate that our initial results with these techniques are promising in successful detection. Discrete wavelet transforms and spectrograms can provide clear visual assistance in detecting Trojans by catching the time-scale differences and time-frequency activities introduced by the Trojans. Furthermore, neural networks with sufficient training are also used and simulation results show that correct decisions are possible with a very high success rate.