Abstract: In this paper, a new face recognition method based on
PCA (principal Component Analysis), LDA (Linear Discriminant
Analysis) and neural networks is proposed. This method consists of
four steps: i) Preprocessing, ii) Dimension reduction using PCA, iii)
feature extraction using LDA and iv) classification using neural
network. Combination of PCA and LDA is used for improving the
capability of LDA when a few samples of images are available and
neural classifier is used to reduce number misclassification caused by
not-linearly separable classes. The proposed method was tested on
Yale face database. Experimental results on this database
demonstrated the effectiveness of the proposed method for face
recognition with less misclassification in comparison with previous
methods.
Abstract: In first stage of each microwave receiver there is Low
Noise Amplifier (LNA) circuit, and this stage has important rule in
quality factor of the receiver. The design of a LNA in Radio
Frequency (RF) circuit requires the trade-off many importance
characteristics such as gain, Noise Figure (NF), stability, power
consumption and complexity. This situation Forces desingners to
make choices in the desing of RF circuits. In this paper the aim is to
design and simulate a single stage LNA circuit with high gain and
low noise using MESFET for frequency range of 5 GHz to 6 GHz.
The desing simulation process is down using Advance Design
System (ADS). A single stage LNA has successfully designed with
15.83 dB forward gain and 1.26 dB noise figure in frequency of 5.3
GHz. Also the designed LNA should be working stably In a
frequency range of 5 GHz to 6 GHz.