Design Of Low Pass Fir Filter

There are many different types of filters that can be used for decimating, including: cascaded comb-integrator (CIC); direct form polyphase finite impulse response (FIR); half-band FIR; symmetric polyphase FIR filters; transposed direct form II infinite impulse response (IIR) and quasi-linear IIR filters amongst others. As well as using these different configurations, hybrid types can be used for more efficient implementations designed either for better magnitude response, lower power consumptions or

Due to the time domain sampling effect, the discrete time channel impulse response is given by

Figure 10 shows the results between the hybridg algorithm compared to other algorithms with various mathematical functions as presented by privous sessions. It is cleard to see that the hybride algorithm performed better than other techniques. Surrprisingly, the Ackley function performed closely to the hybride algorithm. Figure 11 - 14 shows that PSO reached the optimal result very quickly because this algorithm works as a local search which makes a narrow space for the search of a solution, rather than other algorithms which work as a global search

Apart from the single objective functions considered for this problem, a combined function is also used to perform the multi-objective optimization for the FMS parameters. The function and the variable limits are given using following function. Equal weights are considered for all the responses in this multi-objective optimization problem. Hence W1 and W2 are equal to 0.5.

Filters can either emphasize or reduce some frequencies from a signal. There are different types of filters that can be used. There are different types of filters that can be used. There are also filters that can reject frequencies within a certain frequency band e.g. band bass or band reject.

The proposed filter is an efficient, high-performance and flexible filter. Because of frequency selective nature of BPF, it is used mainly in reception device for electromagnetic interference reduction. Also the nearer frequency channels are separate out by proper filtering at particular frequency

In GSO, each glow worm, agent, carries a light on two dimensional works space and has its own vision, called local-decision range. The luciferin level is associated with the objective value of the agent’s position. The brighter agent means that it flies to a better position (has a better objective value).The agent is only attracted by a neighbor whose luciferin intensity is higher than its own within the local decision range and then flies towards the neighbor. The local-decision range depends on the number of neighbors. While the neighbor-density is low, the range is enlarged in order to find more neighbors, otherwise the range is reduced. The agent always changes its moving direction according to which neighbor is selected. The higher luciferin level the neighbor has, the more attraction which gains. Finally, most agents willget together at the multiple locations. Briefly, the GSO involves in three main phases: luciferin update phase, movement phase, and decision range update.

Step 2: PSO is initialized with a group of random particles. Each particle has its own position, velocity, and best position called personal best position. Each particle will be updated by its own personal best position and global best position. Personal best position is the best position the particle itself has ever reached and global best position is the best one obtained by any particle in the whole group.

C. B. Prakash and R. S. N. Naik, "Tuning of PID Controller by Ziegler-Nichols Algorithm for Position Control of DC Motor," International Journal of Innovative Science, Engineering & Technology, vol. 1, no. 3, pp. 379–382, May 2014.

These algorithms have their own positives and negatives. New algorithms are evolving day by day. Two algorithms listed below are discussed in this essay.

Benchmark functions used are minimization functions and are subdivided into the two groups i.e., unimodal and multimodal. Multimodal functions are also categorized into fixed dimension and high dimension multimodal functions. GSA is a heuristic optimization algorithm which has been gaining interest among the scientific community recently. GSA is a nature inspired algorithm which is based on the Newton’s law of gravity and the law of motion. GSA is grouped under the population based approach and is reported to be more intuitive. The algorithm is intended to improve the performance in the exploration and exploitation capabilities of a population based algorithm, based on gravity rules. However, recently GSA has been criticized for not

Its implementation is very easy but its difficulty in calibration and maintains increases as the order of filter increases.one can easily design and modify a filter using digital signal processing (DSP).Filter function in digital signal processing (DSP) is software based, flexible and repeatable. In digital signal processing (DSP) filter with higher order only require software modification .whereas in analogue circuit we need additionally hardware implementation also. In short digital signal processing (DSP) is defined as the converting the continuously changing waveform (analog) into a series of discrete levels

Power system is a large electrical network used for generation, transmission and distribution of electrical power. Electrical

3.1.2 Active Filters: It inject equal and opposite harmonics onto the power system to cancel those generated by other equipment. Remarkable advances in the field of power electronics had sparked interest in APF for harmonic distortion mitigation. The basic technology of APF is to use power electronics technologies to produce the harmonic current components such that the source will supply only the fundamental part of

Nowadays, along with the development of the world, people now want to do much more complicated work. In order to handle these prolems, the systems of robot have een developed. Just like human, robots are always better when they work as a group, this is when the communication and coordination algorithms need to be applied. To have a better look about this systems, we need to understand clearly the term “ Swarm Robotics ” .