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Adaptive filters are used in the situation where the filter coefficients have to be changed simultaneously according to the requirement. Adaptive filters are needed for fast convergence rate and low mean square error. Many algorithms have been proposed and proved that they have better convergence speed and tracking abilities. This paper shows the ability of adaptive filter for noise cancellation i.e., estimating the desired speech corrupted by unwanted signal i.e., noise. This paper is going to compare the performance of adaptive algorithms for noise cancellation in real time signals like recorded speech with different background noise. In the existing papers the authors have taken the input signal as sinusoidal signal etc. In order to measure the performance step size is the main factor for the convergence speed and mean square error. Many analyses proved that RLS algorithm had faster convergence speed and smaller steady state error compared with basic LMS algorithm and normalized LMS algorithm (NLMS). The existing simulation results enable to measure the performance of filter and show the convergence speed improvement when using RLS algorithm, NLMS algorithm and LMS algorithm.

Form the past several decades' noise cancellation in speech signal gains researchers' attention. Several techniques were developed for noise cancellation among them optimal wiener filter can be the one of the most fundamental approach for noise cancellation. Later on adaptive filter was introduced to attain better performance. This paper shows the capacity of wiener filter and adaptive filter for removal of noise by estimating the signal by means of removing the noise signal form the corrupted signal.Wiener filter plays a central role in wide range of applications such as linear prediction, echo cancellation, signal restoration, channel equalization and system identification. In this paper the performance of wiener filter and adaptive filter for removal of noise in the presence of real time environment are compared. In the existing papers the authors have proposed the theory of wiener filter and adaptive filter algorithms in real time environment like recorded speech. So this is paper is going to take the part of the existing paper and going to perform the noise cancellation. In order to measure the performance step size is the main factor for the convergence speed and mean square error. Wiener filter provides better performance for noise cancellation but it requires large no. of computations i.e., complexity and cost of the system is going to increase, so adaptive filter is the alternate approach for removal of noise with moderate complexity and cost. The simulation result clearly shows that wiener filter gives the better performance but due to high cost adaptive filter is the choice of many applications. This paper is going to discuss about wiener filter theory, wiener filter problem, solution to optimal filtering, adaptive filtering, adaptive algorithm, study of wiener filter and adaptive filter for noise reduction etc.

An ad hoc network is a mobile wireless network that has no fixed access point or centralized infrastructure. Each node in the network functions as a mobile router of data packets for other nodes and should maintain the network routes for long standing which is not possible due to limited battery source. Also, due to node mobility, link failures in such networks are very frequent and render certain standard protocols inefficient resulting in wastage of power and loss in throughput. The power consumption is an important issue with the goal to maintain the network lives for long by consuming less power. The power consumption can be achieved by modifying algorithms such as cryptographic algorithms,Routing algorithms, Multicast Algorithms, Energy Efficient Algorithms and Power Consumption Techniques in High Performance Computing, Compression and decompression algorithms, minimizing link failure algorithms, and by power control algorithms. In this work, we have proposed a new algorithm for minimization of power consumption in Ad hoc networks. The performance of the proposed model is analyzed and it is observed that, information could be sent with security consuminglesscomputational power, thereby increasing the battery life.

Mobile Ad hoc Networks (MANETs) are wireless infrastructure less networks can be easily formed or deployed due to its simple infrastructure. Since each node acts as a router, the nodes must assist in discovery and maintain the network routes for long standing which is not possible due to limited battery source. This reflects on link failures which increase the overhead. Since the MANETs has tremendous applications in commercial, military, mobile conferencing outside the office, battlefield communications, embedded sensor devices that automate household functions, etc., the goal is to maintain the network sustain for long by reducing power consumption. The power consumption plays a vital role in MANETS, and there are lots of low power consumption techniques were designed. Among many, data compression technique is a simple technique, with the benefit of reducing the transmission rate that consumes less bandwidth and low power. Hence in this work, Lempel-Ziv-Welch (LZW) compression algorithm is implemented and the simulation results proved that the data can be transmit with low power consumption without any loss of data. This, in turn helps in reducing the battery consumption, thereby increasing the battery life.