Quantization

IMPLEMENTATION OF ROBUST SAMPLING IN WIRELESS SENSOR NETWORKS FOR ENERGY CONSERVATION Importance and Relevance and Novelty of the Project: 1. About Wireless Sensor Networks Now-a-days, deployment of wireless sensor networks for real-time applications has increased a lot. As and when, we talk about monitoring, transmitting (wireless), and controlling various physical conditions at a site, which we basically call a smart system, can be easily achieved by the wireless sensor networks. A wireless sensor

real numbers, we need to quantize these transmission probability gain to run the dynamic optimization procedure i.e., \begin{equation} \Delta Y_k = \mathop {\min }\limits_{\forall i,j;i \ne j} \left| {Y_i - Y_j} \right|, \end{equation} with the quantization step of ${\rm N} = \left[ {\frac{H}{{\Delta Y_k}}} \right]$. The nodes are divided into ${L}$ steps and we decide whether node $j$ is selected

Our algorithm also finds the optimal solution with an increased complexity, when the network becomes more homogeneous or less heterogeneous due to increasing ${\rm N}$. The quantization precision ${\rm N}$ in Algorithm 1, is a physical quantity specified by the underlying network that elaborate the designing of quantization step. The total content size $H$ depends on the required content transmission rate $r_{c_i, d_i}$ and $Y_k$, whereas $Y_k \sigma$ are defined by the contact dynamics of the nodes

frequency in both directions is the DC coefficient and the rest are called as AC coefficients. QUANTIZATION IN JPEG Quantization is a lossy step where we loose data. The DCT is a lossless procedure , the data undergoing through this procedure can be precisely recovered through the IDCT . During Quantization every coefficients in the (8×8) DCT matrix is divided by its corresponding quantization value. The quantized coefficient and the reverse quantized coefficient can be achieved by the following

An analog signal is a continuous signal in which the time varying signal is a representation of some other time varying quantity i.e. in an audio signal, the instantaneous voltage of the signal varies with the pressure of the sound waves Analog signal processing is a type of signal processing conducted on which continuous analog signals by some analog means The difference between the analog and digital signal processing is that analog signal has continuous values unlike the digital which has discrete

this paper we present a voice recognition system based on Mel Frequency Cepstral Coefficients (MFCC) and vector Quantization (VQ). This technique has an advantage that it creates fingerprint of human voice by exploiting human acoustic system and cepstral analysis. MFCC is widely accepted as a baseline for voice recognition due to these unique features. KeywordsMFCC, Vector Quantization, Speaker recognition, Feature extraction, Fast Fourier Transform Introduction Human speech is the most natural

Design of Continuous Time Second Order Sigma-Delta Modulator Using Feedback Element Mr. Ravinder Choudhary University Institute of Engineering and Technology Kurukshetra University Kurukshetra, India E-mail- erravindera@gmail.com Abstract: This paper discuss the continuous time second order Sigma-Modulator with the

power consumed is 800mw. In this design the comparators are realized with the inverters, which avoids the complexity in the design of conventional comparators. The TIQ comparator consists of two cascaded CMOS inverters. The analog input signal quantization level is set in the first stage by changing the VTC by means of transistor sizing. The second inverter stage is used for increased gain and logic level inversion so that the circuit behaves as an internally set comparator circuit. The key point

DIGITAL SATELLITE COMMUNICATION SYSTEMS By Oyudo Richard Chidiebube (Matriculation Number: 110805082) Department of Computer Sciences University of Lagos (Ref: CSC422/2014-15) ABSTRACT Modern wireless communications technology has almost become synonymous with digital satellite communications. It is hence, a key element in the current era of globalization as it has so largely been adopted as a primary means of communication. This paper attempts to investigate modern digital satellite communications

Before approaching Claude Shannon’s contribution to Cryptography, one must look at his prior work in particular in the field of information theory, a field he theorized in his 1948 paper A Mathematical Theory of Information. Shannon introduced a lot of the ideas that were mentioned and developed in this revolutionary paper to the scientific community in his 1945 paper entitled A Mathematical Theory of Cryptography. Indeed, during the Second World War, Shannon decided to join the Bell Labs, a research