Electrical and Electronics

A Broadband multilayer antenna for C-Band applications is presented in this paper. The proposed antenna is composed of a FR-4 and air gap Dielectric material, two square slots, two L-Slot, and a Radom. By introducing the two parts, the impedance bandwidth of the antenna can be significantly enhanced. Analysis done with and without ground plane. Simulation results show that the proposed antenna can operate from 3.2GHz to 4.8 GHz with low VSWRs ? 2. Stable antenna gain (dB) is also achieved over the entire operating frequency band. Furthermore, the size of the proposed antenna is very compact, which is only at the centre of the operating frequency band.

The concept of smart grid is a promising issue in the field of energy management. There are lots of researches going on different aspect of this system. One of the major topics that is involved in this concept is the communication constraints. In this paper we have analyzed few aspects of smart grid system. The main focus is on the communication technologies and their threats along with solutions. We have considered different literatures to investigate the overall concept of smart grid and prepared a review on the topic.

This paper presents comparative study of Hybrid Multilevel Inverter in continuation to previous paper. Different distinct topologies of multilevel inverters for power circuits used in Hybrid Multilevel Inverter are discussed. The comparison is done with respect to different performance index like switching devices, power applications and modulation techniques used. Different topologies are discussed and reviewed in brief.

The OFDM based architectures severely suffers with the Impairments like IQ imbalance and Carrier Frequency Offset (CFO). These impairments lead to Inter Carrier Interference (ICI). It causes reduction in the performance of the systems in terms of Bit Error Rate (BER). In this paper we propose an adaptive equalizer to compensate for these impairments caused at Tx and Rx while considering Inter Block Interference (IBI) due to mismatch between Cyclic Prefix (CP) and Channel Impulse Response. If the cyclic prefix is sufficient an LMS based adaption with 2 tap is proposed which converges easily. In case of lesser length of CP a Frequency domain Per Tone Equalizer (PTEQ) is proposed which uses separate T-taps for each tone unlike Time domain Equalizer (TEQ) which equalizes all tones jointly and limits the system performance. This proposed equalizer thus increases the delay of channel response and hence reduces the IBI. The frequency domain equalizer after FFT will perform well and the simulation results shows that both the equalizers BER values are very near to the curves for ideal case.

This paper presented a study of four algorithms, the equalization algorithm to equalize the transmission channel with ZF and MMSE criteria, application of channel Bran A, and adaptive filtering algorithms LMS, NMLS and RLS to estimate the parameters of the equalizer filter, i.e. move to the channel estimation and therefore reflect the temporal variations of the channel, and reduce the error in the transmitted signal. So far the performance of the algorithm equalizer with ZF and MMSE criteria both in the case without noise, a comparison of performance of the LMS, NLMS and RLS algorithm.

A coding scheme for OFDM transmission is proposed, exploiting a connection between pairs of Golay complementary sequences and second-order Reed-Muller codes. Using a realization of 16-QAM or 64 QAM constellation as the vector sum or two or three QPSK constellation respectively we construct 16 QAM and 64 QAM sequences having low PAPR. In this paper, we further examine the squared Euclidean distance of these M-QAM sequences and their variations. Our aim here is to combine the block coded modulation (BCM) and Golay complementary sequences to trade off the PAPR, the code rate, and the squared Euclidean distance of M-QAM OFDM signals

Induction motors plays a vital role in almost all the industrial drive systems because of their simple, efficient and robust nature offering high degree of reliability. These machines face various stresses during operating conditions which may lead to different types of faults. Hence condition monitoring and maintenance becomes necessary in order to avoid unexpected failures. Different fault monitoring techniques for induction motors can be broadly categorized as model based techniques, signal processing techniques, and artificial intelligence based soft computing techniques. The traditional model based diagnostic techniques provides a good detection of the fault in the machine but nowadays artificial intelligence techniques have been introduced to overcome the existing inaccuracy. Soft computing techniques enable better analysis of a faulty system even if models are inaccurate. Besides giving improved performance these techniques are easy to extend and modify. This paper provides a comprehensive study of conventional and innovative techniques. Keywords: Induction motor, motor faults, diagnostic techniques

Brushless Direct Current (BLDC) motors are one of the motor types rapidly gaining popularity. BLDC motors are used in industries such as Appliances, Automotive, Aerospace, Consumer, Medical, Industrial Automation Equipment and Instrumentation. As the name implies, BLDC motors do not use brushes for commutation; Instead, they are electronically commutated. This paper is focused on the various methods of testing and various tests both during construction and after construction is done on BLDC motors. These tests include: measurement of coil resistance, measurement of air gap, vibration testing, magnetic saturation, temperature experiments and etc. For a large number of experiments, The proposed method has been described for the size and various types of BLDC motors that in different conditions the motor is encountered.

This paper describes a hybrid design for intrusion detection that combines anomaly detection with misuse detection. The proposed method includes an ensemble feature selecting classifier and a data mining classifier. The former consists of four classifiers using different sets of features and each of them employs a machine learning algorithm named fuzzy belief k-NN classification algorithm. The latter applies data mining technique to automatically extract computer users’ normal behavior from training network traffic data. The outputs of ensemble feature selecting classifier and data mining classifier are then fused together to get the final decision. The experimental results indicate that hybrid approach effectively generates a more accurate intrusion detection model on detecting both normal usages and malicious activities.

This paper is about designing a 15 tap 8-bit FIR filter using Direct form II. Serial Architecture is used for Multiplication and Accumulation. Entire Design is created in structural manner using verilog models from fsa0m a library. Delay balancing technique is used for reducing glitches in Multiplier.