Radar Signal Recovery using Compressive Sampling Matching Pursuit Algorithm

In this study, we propose compressive sampling matching pursuit (CoSaMP) algorithm for sub-Nyquist based electronic warfare (EW) receiver system. In compressed sensing (CS) theory time-frequency plane localisation and discretisation into a N×N grid in union of subspaces is established. The train of radar signals are sparse in time and frequency can be under sampled with almost no information loss. The CS theory may be applied to EW digital receivers to reduce sampling rate of analog to digital converter; to improve radar parameter resolution and increase input bandwidth. Simulated an efficient approach for radar signal recovery by CoSaMP algorithm by using a set of various sample and different sparsity level with various radar signals. This approach allows a scalable and flexible recovery process. The method has been satisfied with data in a wide frequency range up to 40 GHz. The simulation shows the feasibility of our method

Image Denoising by using Modified SGHP Algorithm

In real time applications, image denoising is a predominant task. This task makes adequate preparation for images looks prominent. But there are several denoising algorithms and every algorithm has its own distinctive attribute based upon different natural images. In this paper, we proposed a perspective that is modified parameter in S-Gradient Histogram Preservation denoising method. S-Gradient Histogram Preservation is a method to compute the structure gradient histogram from the noisy observation by taking different noise standard deviations of different images. The performance of this method is enumerated in terms of peak signal to noise ratio and structural similarity index of a particular image. In this paper, mainly focus on peak signal to noise ratio, structural similarity index, noise estimation and a measure of structure gradient histogram of a given image

Universal Electro-Optical Hybrid Logic Gates

An Electro-Optical Hybrid Logic Gate is defined as a circuit which accepts either electrical or optical signals and produces both electrical and optical signals. This paper explores the feasibility to develop universal hybrid NOR and NAND gates which can be used for implementing any basic gate like AND, OR, or any complex logic function. These hybrid logic gates are proposed and implemented using phototransistors and LEDs. The logic circuits are found to be working satisfactorily for the defined logic levels

On the interesting course of dichloroketene addition to 1,5-dimethyl-1,5-cyclooctadiene

Reaction of dichloroketene with 1,5-dimethyl-1,5 COD 6 charters an eventful course to furnish novel tricyclic ketone 10, through the intermediacy of tricyclic hydroxy olefin 9, in which the two carbon atoms of dichloroketene form a bridge across the eight mem-bered ring

Voice Conversion by Prosody and Vocal Tract Modification

In this paper we proposed some exible methods, which are useful in the process of voice conversion. The pro-posed methods modify the shape of the vocal tract system and the characteristics of the prosody according to the de-sired requirement. The shape of the vocal tract system is modied by shifting the major resonant frequencies (for-mants) of the short term spectrum, and altering their band-widths accordingly. In the case of prosody modication, the required durational and intonational characteristics are im-posed on the given speech signal. In the proposed method, the prosodic characteristics are manipulated using instants of signicant excitation. The instants of signicant excita-tion correspond to the instants of glottal closure (epochs) in the case of voiced speech, and to some random excita-tions like onset of burst in the case of nonvoiced speech. Instants of signicant excitation are computed from the Lin-ear Prediction (LP) residual of the speech signals by using the property of average group delay of minimum phase sig-nals. The manipulations of durational characteristics and pitch contour (intonation pattern) are achieved by manipu-lating the LP residual with the help of the knowledge of the instants of signicant excitation. The modied LP residual is used to excite the time varying lter. The lter parameters are updated according to the desired vocal tract characteris-tics. The proposed methods are evaluated using listening tests. 1

Intonation modeling for Indian languages

Abstract In this paper we propose models for predicting the intonation for the sequence of syllables present in the utterance. The term intonation refers to the temporal changes of the fundamental frequency ðF 0 Þ. Neural networks are used to capture the implicit intonation knowledge in the sequence of syllables of an utterance. We focus on the development of intonation models for predicting the sequence of fundamental frequency values for a given sequence of syllables. Labeled broadcast news data in the languages Hindi, Telugu and Tamil is used to develop neural network models in order to predict the F 0 of syllables in these languages. The input to the neural network consists of a feature vector representing the positional, contextual and phonological constraints. The interaction between duration and intonation constraints can be exploited for improving the accuracy further. From the studies we find that 88% of the F 0 values (pitch) of the syllables could be predicted from the models within 15% of the actual F 0 . The performance of the intonation models is evaluated using objective measures such as average prediction error ðlÞ, standard deviation ðrÞ and correlation coefficient ðcÞ. The prediction accuracy of the intonation models is further evaluated using listening tests. The prediction performance of the proposed intonation models using neural networks is compared with Classification and Regression Tree (CART) models