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Continuous mode class-J radio-frequency (RF) power amplifier is a promising technique that extends the operating bandwidth of the conventional class-B power amplifier. However, the maximum theoretical efficiency is limited to that of the class-B power amplifier. In this paper, an enhanced mode of operation for the class-J power amplifier is proposed by incorporating a third harmonic voltage component to produce an optimum waveform for maximizing the fundamental voltage component and thereby to increase the drain efficiency and introduce a new design space. A detailed derivation for the necessary relations of output power, drain efficiency, and the required harmonic load impedances is provided, showing a significant improvement in theoretical maximum efficiency from 78.5 to 89.8%. In order to confirm the developed analytic approach, a 10 W prototype amplifier model was designed and fabricated to operate within the global system for mobile communications (GSM) frequency band 850–950 MHz using a commercial GaN power high electron mobility transistor (HEMT). The experimental results have indicated that the drain efficiency of the circuit varies from 68 to 80% within the desired band.

This paper proposes an improved chaos-based M-ary modulation system. It reproduces deterministic chaotic dynamics to create M-ary non-coherent modulation. The proposed modulation system transmits data using autonomous chaotic sequences. It separates the chaotic dynamics through the use of interleavers and realigns them through the use deinterleavers. The simulation results show that the improved scheme overperforms its traditional counterpart. The degree of improvement grows as the M-ary order is increased, with a penalty of increased system complexity.

Continuous inverse class-F (CICF) is a recent mode of harmonically-tuned RF power amplifiers used to extend the operating bandwidth of the conventional narrowband class-F−1 power amplifier by producing variable set of drain current waveforms and load admittances that give the same operating efficiency. In this work, a new approach of analysis is developed by suggesting some modified drain current waveforms and comparing the resulting theoretical performance characteristics such as drain efficiency and output RF power with the conventional type. It has been shown that the drain current with a truncated square wave shape can better model the actual behavior of the power amplifier, delivering a theoretical efficiency higher by about 8% than the conventional shape. Besides, a simple analytic technique for extracting the device harmonic load impedances for the desired band is also presented. Based on the theoretical analysis, a 6 W power amplifier circuit was designed and simulated to operate within the frequency band 800 – 1000 MHz. Simulation results indicated that a drain efficiency of values between 82% and 86% was obtained across the specified band.

Video summarization used in many applications such as video object recognition and classification. Different methods used for this purpose: key frame extraction using edge detection and key frame extraction using discrete wavelet transform (DWT). In video processing, numerous frames containing similar information, this leads to time consumption and slow processing speed and complexity. New method Hybrid DWT-Edge Key Frame Detection (HDEKFD) of dynamic sign language presented in this paper. This method combined two algorithms edge detection and DWT to increase processing speed by reduce the numbers of redundant frames. Simulation results illustrate the efficient of the proposed algorithm compare to other methods.

The hidden Markov model (HMM) has recently achieved impressive success in the field of pattern recognition, but some limitations and drawbacks restrict its performance. In this study, a new simple model is proposed to overcome the restrictions of HMM with a high reduction in the computational complexity. The training algorithm of the proposed model is built without iterations. It depends on the number of occurrences of each symbol in the training array, in case the discrete data form is used. However, for the continuous form, it uses the mean and covariance of the training data. On the other hand, the log-likelihood and the Mahalanobis distance are employed in the testing algorithm for indicating the highest matching between the testing data and the training parameters. This new model has been tested for face recognition; the experiments exhibit its advantage in terms of memory usage and processing time requirements, as well as recognition rate.

This paper presents the recognition of digital signal modulation by combining four cumulants as signal features and a threshold discriminator assigned for each cumulant. In this paper, the problem of recognition has been solved by finding a suitable relationship among these features and their classifier. The decision of each classifier has been compared with other classifier outputs. Then, the classifier with the highest priority has been considered as the final efficient decision. The priority of each classifier is based on how its cumulant is robust against a wide range of signal to noise ratio (SNR), for different types of digital modulations under investigation. Many types of quadrature amplitude modulation (16, 32, 64, 128, and 256) have been recognized with low SNR down to −5 dB. Using such combination, the average recognition percentage was increased with low SNR. The recognition gained 81.166%–100% for 4096 samples while the percentages are from 86.9% to 98.6% with a variable number of sam...

An effective error-correction scheme based on normalized correlation for a non coherent chaos communication system with no redundancy bits is proposed in this paper. A modified logistic map is used in the proposed scheme for generating two sequences, one for every data bit value, in a manner that the initial value of the next chaotic sequence is set by the second value of the present chaotic sequence of the similar symbol. This arrangement, thus, has the creation of successive chaotic sequences with identical chaotic dynamics for error correction purpose. The detection symbol is performed prior to correction, on the basis of the suboptimal receiver which anchors on the computation of the shortest distance existing between the received sequence and the modified logistic map’s chaotic trajectory. The results of the simulation reveal noticeable Eb/No improvement by the proposed scheme over the prior to the error- correcting scheme with the improvement increasing whenever there is increase in the number of sequence N. Prior to the error-correcting scheme when N=8, a gain of 1.3 dB is accomplished in Eb/No at 10-3 bit error probability. On the basis of normalized correlation, the most efficient point in our proposed error correction scheme is the absence of any redundant bits needed with minimum delay procedure, in contrast to earlier method that was based on suboptimal method detection and correction. Such performance would render the scheme good candidate for applications requiring high rates of data transmission.

The important task in the computer interaction is the languages recognition and classification. In the Arab world, there is a persistent need for the Arabic spoken language recognition To help those who have lost the upper parties in doing what they want through speech computer interaction. While, the Arabic automatic speech recognition (AASR) did not receive the desired attention from the researchers. In this paper, the Radial Basis Function(RBF) is used for the improvement of the Arabic spoken language letter. The recognition and classification process are based on three steps; these are; preprocessing, feature extraction and classification (Recognition). The Arabic Language Letters (ALL) recognition is done by using the combination between the statistical features and the Temporal Radial Basis Function for different letter situation and noisy condition. The recognition percent are from 90% - 99.375% has been gained with independent speaker, where these results are over-perform the earlier works by nearly 2.045%. The simulati.on has been made by using Matlab 2015b.

Radar is a promising device for detection and recognition of invisible moving objects, Where, the micro-Doppler frequency shift caused by moving the object's parts have been represented as an attractive feature in the recognition process. In spite of that, no thorough analysis of human movement by bicycle and no discriminate from the running one through the wall in the literature. This paper presents a mathematical model of bicycle movement, then, the recognition of moving objects through the wall. Where three human movements; walking, running and on a bicycle have been recognized through two types of wall wood and cork. The theoretical analysis and measured was given a recognition 98.7% for human walking on his feet, 99% of the passenger on a bicycle, and 98% of the person running have been achieved without walls. While, a 95.4%, 96.2%, and 95% recognition have been gained from walking, moving by bicycle and running with wooden wall and 94%, 94.8%, and 93.3% respectively with cork wall. 2.4 GHz as a detector and SVM as classifier are used.

Video summarization used for a different application like video object recognition and classification. In video processing, numerous frames containing similar information, this leads to time consumption and slow processing speed and complexity. By using key frames reducing the amount of memory needed for video data processing and complexity greatly. In this paper key frame extraction of Arabic isolated word using discrete wavelet transform (DWT) with modified threshold factor is proposed with different bases. The results for different wavelet basis db, sym and coif show the best result for numbers of key frames at the threshold factor value (0.75).