Asian Journal of Electrical Sciences (AJES) is a quarterly international peer-reviewed journal of Electrical Sciences. One of the objectives of this journal is to disseminate knowledge on various research issues connected with the topics include, but are not limited to:

Telecommunications – transmission of information, coax cable, optical fiber or free space, amplitude modulation and frequency modulation, transmitters and receivers, transceiver.
Instrumentation – pressure, flow and temperature, electromagnetic theory, thermocouples, sensors of larger electrical systems, control engineering.
Computers – Computers and computer systems, hardware, software, software engineering.

Power engineering – generation, transmission and distribution of electricity, transformers, electric generators, electric motors, high voltage engineering and power electronics.
Control engineering – dynamic systems, design of controllers, electrical circuits, digital signal processors, microcontrollers and PLCs (Programmable Logic Controllers), industrial automation. Electronic Engineering -Electronic circuits, resistors, capacitors, inductors, diodes and transistors, radio engineering, radar, television, audio systems, computers and microprocessors.
Microelectronics – Electronic circuit, integrated circuit, semiconductor transistors, resistors, capacitors, inductors, Nanoelectronics.

Signal processing – signals, analog, digital, telecommunications, Digital Signal Processing, SDTV | HDTV sets, radios and mobile communication devices, Hi-Fi audio equipments, Dolby noise reduction algorithms, GSM mobile phones, mp3 multimedia players, camcorders and digital cameras, automobile control systems, noise cancelling headphones, digital spectrum analyzers, intelligent missile guidance, radar, GPS based cruise control systems, image processing, video processing, audio processing and speech processing systems.

In this paper a novel method of de-noising phonocardiogram by time-frequency Overlapping Group Shrinkage method is described. In this method sigma, the standard deviation of the stationary noise present in a noisy phonocardiogram is found using activity detection. This noise is then canceled by attenuating it in the time frequency domain. The accuracy of noise reduction is measured by SNR. Overlapping Group shrinkage algorithm reduces the effect of noise by attenuating them using hard or soft thresholding. Performance of this method was found to be far better compared to other methods such as Soft Thresholding and Block Thresholding.