Finite impulse response (FIR) filter implementations abound and play a major part in signal processing applications. The FIR filter (FIRF) delivers several benefits, and there exist many different realizations, such as designs using a system generator, normal FIRF, decimator FIRF, genetic algorithm (GA)-based, and parallelbased, among others. Most architectures utilize more hardware with less efficiency. Moreover, these existing architectures did not concentrate on and explored the applications' characteristics. The FIRF affords several paybacks like (i) computational efficiency in multi-rate frameworks, (ii) manageable linear phase response, and (iii) the desirable numerical ability to accomplish finite precision and fractional arithmetic. The digital multi-standard RFIR filter is implemented in wireless applications to decrease the bit error rate (BER). The discrete FIRF can render efficient designs with low-power consumption and high performance. Earlier, hordes of research articles described different FIRF designs without handling signal denoising with an effective multiplier design. Booth's algorithm performs multiplication by multiplying two signed binary numbers in 2's complement notation. The Booth multiplier (BM) overcomes the reduced area drawback, but it would not work with alternation of zeros and ones since it entails more additions and subtractions [1-3]. This problem is overcome by the modified BM (MBM), which contains half the number of partial product rows. It functions well regarding speed and power consumption. On the other hand, its main shortcoming is sloppy work for negative numbers [4, 5].

This project discusses about wheel chair controlled by brain based on Brain–computer interfaces (BCI). BCI’s are systems that can bypass conventional channels of communication (i.e., muscles and thoughts) to provide direct communication and control between the human brain and physical devices by translating different patterns of brain activity into commands in real time. The intention of the project is to develop a robot that can assist the disabled people in their daily life to do some work independent of others. Here, we analyse the brain wave signals. Human brain consists of millions of interconnected neurons, the pattern of interaction between these neurons are represented as thoughts and emotional states. According to the human thoughts, this pattern will be changing which in turn produce different electrical waves. A muscle contraction will also generate a unique electrical signal. All these electrical waves are sensed by the brain wave sensor and different patterns are used for controlling a wheel chair.

This paper presents a high level view of how clusters are being used in large number of domains for preserving and protecting the data. Because of these , clusters are being exposed to many attacks coming from open network.. Hence there are many methods to design a privacy preserving clusters. To ensure these preserving clusters, cluster validity measurements are done for different type of Data. Protocols are used to do the privacy preserving. The clusters analysis are used in banking sector for identification of the bank customer profile. Algorithms are used to find the Sensitive data before making the individual data into clusters of data .and then the privacy is applied only on these sensitive data.