Uncategorized

Solving Linear Equations using QR Decomposition

QR decomposition is another powerful technique to solve linear equations. In QR decomposition, the co-efficient matrix need not to be a symmetric matrix. In special cases where the input signal is compressible or sparse, QR decomposition can directly operate on matrix if less than . This way an underdetermined linear system is solved. Matrix is

Solving Linear Equations using QR Decomposition Read More »

Solving Linear Equations with Modified Cholesky Decomposition

In our previous tutorial, we have discussed about Cholesky decomposition which is a very important matrix factorization to solve a linear equation. But this technique has some drawbacks which are also discussed in the same tutorial. In this tutorial, we will discuss about modified Cholesky Decomposition which is an alternative version of Cholesky decomposition. This

Solving Linear Equations with Modified Cholesky Decomposition Read More »

Solving Linear Equations using Cholesky Decomposition

Cholesky decomposition is a very important matrix factorization technique which is used to solve a linear equation. This technique originally derives from very popular LU decomposition and very suitable for higher order matrices. In Cholesky decomposition, the co-efficient matrix has to be a symmetric positive definite matrix. But in general, the co-efficient matrix can be

Solving Linear Equations using Cholesky Decomposition Read More »

LUT Based Numerically Controlled Oscillator

A numerically controlled oscillator (NCO) is used for on-chip generation of major signals like cosine, sine, linear frequency modulated (LFM), Gaussian etc. in system on chips (SoCs). These signals can be generated by two ways, either by analog circuitry or by digital circuitry. In a digital system, these signals are generated using numerically controlled oscillator

LUT Based Numerically Controlled Oscillator Read More »

Implementation of Logarithm Function

Signal processing algorithms sometimes involve computation of exponential as well as logarithm. Thus it is important to implement both the functions on digital hardware. In our previous tutorials, we have discussed implementation of exponential function. In this work, design of digital hardware to find logarithm of a number is discussed. The logarithm function is computed

Implementation of Logarithm Function Read More »

Computation of Exponential Function

Signal processing algorithms sometimes involve computation of exponential. Thus it is important to implement the exponential function. In this work, design of digital hardware for exponential function is discussed. Like other elementary functions, exponential function is also computed using the iterative formulas. In this work, computation of the exponential function is shown for three cases.

Computation of Exponential Function Read More »

FPGA Implementation of 1024-point FFT/IFFT Processor

I. Introduction Fast Fourier transform (FFT), an efficient technique to perform discrete Fourier transform (DFT), is the most important block in the signal processing domain. FFT is used to convert a signal in time domain to its frequency domain. On the other hand, inverse FFT (IFFT) block is used to convert the signal in frequency

FPGA Implementation of 1024-point FFT/IFFT Processor Read More »

MATLAB Realization of FFT/IFFT w/o Direct Function

Fast Fourier Transform (FFT) is an efficient technique to implement Discrete Fourier Transform (DFT). FFT is used to observe the frequency domain characteristics of a signal or an image. Similarly Inverse FFT (IFFT) is used to convert a frequency domain signal to its time domain. Thus FFT and IFFT are very important functions in the

MATLAB Realization of FFT/IFFT w/o Direct Function Read More »

Shopping Basket