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This paper presents high gain CMOS low noise amplifier (LNA) at 2.4 GHz for Wireless Sensor Network Applications. The proposed LNA is developed in 0.13-µm CMOS process. The cascode topology with source degeneration inductor is employed. The high gain is obtained by using common-source (CS) amplifier at the second stage. The simulation results show that the proposed LNA achieves gain of 23.9 dB, input return loss (S11) of -26.9 dB and output return loss (S22) of -20.6 dB. The noise figure (NF) and the input third order intercept point (IIP3) are 5.6 dB and -11.1 dBm, respectively. The total power consumption is 8.1 mW at 1.2 V supply voltage with the chip size is 0.64 mm² including bond pads.

Palmprint is very popular biometric recognition system that is able to guarantee high accuracy. It has attracted increasing amount of attention because palmprints are abundant of many characteristics, such as the principle lines, ridges, minute points and textures for the use of images with low resolution. In this paper we propose palmprint feature detection based on KAZE technique. Palmprint texture has many important points for discrimination process. Selecting the best number of point using KAZE is very important for classification process in order to avoid overlapping features in different class. The experimental work has been done using polyU palmprint database in order to evaluate the best number of features.