An explicit form of all‐pole filter function with decreasing envelope of the summed sensitivity function

Pavlović, Vlastimir D.

doi:10.1002/cta.653

Cited by 15 publications

(10 citation statements)

References 37 publications

(25 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The summed sensitivity function, Dð!Þ, discussed in Geher (1971), Rau (1967), Moschytz (1974), Milic´Lj and Fidler (1981) and Pavlovic´(2011), is defined as.…”

Section: Explicit Form Of All-pole Filter Functionmentioning

confidence: 99%

New class of filter functions generated most directly by the Christoffel–Darboux formula for classical orthonormal Jacobi polynomials

Pavlović

Ilić

2011

International Journal of Electronics

Self Cite

View full text Add to dashboard Cite

The new originally capital general solution of determining the prototype filter function as the response that satisfies the specifications of all pole low-pass continual time filter functions of odd and even order is presented in this article. In this article, two new classes of filter functions are proposed using orthogonal and orthonormal Jacobi polynomials. The approximation problem of filter function was solved mathematically, most directly applying the summed Christoffel-Darboux formula for the orthogonal polynomials. The starting point in solving the approximation problem is a direct application of the Christoffel-Darboux formula for the initial set of continual Jacobi orthogonal polynomials in the finite interval ½À1, þ1 in full respect to the weighting function with two free real parameters. General solution of the filter functions is obtained in a compact explicit form, which is shown to enable generation the Jacobi filter functions in a simple way by choosing the numerical values of the free real parameters. For particular specifications of free parameters, the proposed solution is used with the same criterion of approximation to generate the appropriate particular filter functions as are: the Gegenbauer, Legendre and Chebyshev filter functions of the first and second kind as well. The examples of proposed filter functions of even and odd order are illustrated and compared with classical solutions.

show abstract

“…The summed sensitivity function, Dð!Þ, discussed in Geher (1971), Rau (1967), Moschytz (1974), Milic´Lj and Fidler (1981) and Pavlovic´(2011), is defined as.…”

Section: Explicit Form Of All-pole Filter Functionmentioning

confidence: 99%

New class of filter functions generated most directly by the Christoffel–Darboux formula for classical orthonormal Jacobi polynomials

Pavlović

Ilić

2011

International Journal of Electronics

Self Cite

View full text Add to dashboard Cite

show abstract

“…The other studies utilized iterative clipping and filtering by placing IDFT and the DFT blocks many times in different locations within the OFDM system, hence, increasing the computational complexity. As examples of the filters, see . The performance of the CAC technique has been analyzed in the literature , so we will not concentrate on re‐producing such analysis in this paper.…”

Section: Cac Techniquementioning

confidence: 99%

Reducing the power envelope fluctuation of OFDM systems using side information supported amplitude clipping approach

Taher

Mandeep

Ismail

et al. 2013

Circuit Theory & Apps

View full text Add to dashboard Cite

OFDM is an important modulation technique currently in development in the field of communications systems. OFDM signals can combat multipath propagation and fading channels and can support large data rates. However, OFDM systems are multicarrier systems and experience problems due to the required summation of sinusoids when the in‐phase subcarriers are combined, which produces high power peaks. The large power envelope fluctuations that occur at the output cause in‐band and out‐of‐band distortions that result in degraded BER performance. The literature contains many qualified approaches to resolving the peak‐to‐average power ratio problem, including selected mapping, partial transmit sequence, and amplitude clipping techniques. The simplest technique is the amplitude clipping technique, and the selected mapping and partial transmit sequence techniques are excessively complicated for real‐time implementation. In this paper, we suggest a modification to the amplitude clipping method to produce a novel clipping technique called the side information supported amplitude clipping (SI‐SAC) method. The SI‐SAC technique involves sending certain bits of extra information so that the receiver can recover all of the clipped data. The SI‐SAC technique does not add computational complexity to the system, and simulation results show that the proposed method is superior to the conventional method. The peak‐to‐average power ratio was reduced by ≈2.5 dB, and the magnitude of the mean squared error vector is the same as that of the original signal that is not clipped. In contrast, the conventional amplitude clipping method produces a mean squared error vector with a large magnitude. Copyright © 2012 John Wiley & Sons, Ltd.

show abstract

“…The integral cannot be solved because the function pP is unknown. Nevertheless, the partial derivatives can be defined according to equations (9) and (10), as shown in Figure 6. The unknown function is replaced by the corresponding polynomial in the last step, by substituting the head of the function (name of the function) by the appropriate symbol for the special function.…”

Section: Automated Building Knowledge For Generation Of Transfer Funcmentioning

confidence: 99%

Automated knowledge based filter synthesis using modified Chebyshev polynomials of the first kind

Pavlović

Lutovac

2012

FACTA U EE

View full text Add to dashboard Cite

The paper presents the automated design of active RC and programmable filters. The approximating function is derived using Chebyshev orthogonal polynomials of the first kind. Optimization is performed using symbolic manipulation of expressions inputted into computer algebra system. The code is in the form of template notebook, and the user should specify the minimal number of numeric values, such as the number of second-order filter sections, the pass-band edge frequency, the reflection coefficient, and the preferred values of component values.

show abstract

An explicit form of all‐pole filter function with decreasing envelope of the summed sensitivity function

Cited by 15 publications

References 37 publications

New class of filter functions generated most directly by the Christoffel–Darboux formula for classical orthonormal Jacobi polynomials

New class of filter functions generated most directly by the Christoffel–Darboux formula for classical orthonormal Jacobi polynomials

Reducing the power envelope fluctuation of OFDM systems using side information supported amplitude clipping approach

Automated knowledge based filter synthesis using modified Chebyshev polynomials of the first kind

Contact Info

Product

Resources

About