Analysis and optimization of noise in continuous-time OTA-C filters

Koziel, Slawomir; Schaumann, R.; Xiao, Haiqiao

doi:10.1109/tcsi.2005.849142

Cited by 18 publications

(25 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In contrast, this section provides complete, explicit, and easily evaluated formulas based on a general approach to noise analysis, and using matrix description as presented in Section 2, originally presented in [41]. We recall them here for the sake of completeness.…”

Section: Noise Analysis In General Ota-c Filtersmentioning

confidence: 99%

A general framework for evaluating nonlinearity, noise and dynamic range in continuous‐time OTA‐C filters for computer‐aided design and optimization

Koziel

Ramachandran

Szczepański

et al. 2006

Circuit Theory & Apps

Self Cite

View full text Add to dashboard Cite

SUMMARYEfficient procedures for evaluating nonlinear distortion and noise valid for any OTA-C filter of arbitrary order are developed based on matrix description of a general OTA-C filter model. Since those procedures use OTA macromodels, they allow us to obtain the results significantly faster than transistor-level simulation. On the other hand, the general OTA-C filter model allows us to apply matrix transforms that manipulate (rescale) filter element values and/or change topology without changing its transfer function. Due to this, the proposed procedures can be used in direct optimization of OTA-C filters with respect to important characteristics such as noise performance, THD, IM3, DR or SNR. As an example, a simple optimization procedure using equivalence transformations is discussed. An application example of the proposed approach to optimal block sequencing and gain distribution of 8th order cascade Butterworth filter is given. Accuracy of the theoretical tools has been verified by comparing to transistor-level simulation results and to experimental results.

show abstract

Section: Noise Analysis In General Ota-c Filtersmentioning

confidence: 99%

A general framework for evaluating nonlinearity, noise and dynamic range in continuous‐time OTA‐C filters for computer‐aided design and optimization

Koziel

Ramachandran

Szczepański

et al. 2006

Circuit Theory & Apps

Self Cite

View full text Add to dashboard Cite

show abstract

“…Sun (&) School of Engineering and Technology, University of Hertfordshire, Hatfield Herts AL10 9AB, UK e-mail: y.sun@herts.ac.uk delay sensitivity than the LF filter, but it is the worst in other performances. References [27,28] have simulated noise performance for other types of characteristics such as Chebyshev and Bessel and other orders of filters such as 3rd-order and 5th-order at the filter output and input respectively, which all support the result that IFLF filters have higher noise than LF and cascade filters as in [26]. For sensitivity comparison, references [29,30] considered different-order Chebyshev filters and 3rd-order elliptic filters using the integrals of Schoffler's measure and confirmed that LF does have lower sensitivity than the IFLF.…”

Section: Introductionmentioning

confidence: 99%

Performance comparison of high-order IFLF and LF linear phase lowpass OTA-C filters with and without gain boost

Hasan

Sun

2009

Analog Integr Circ Sig Process

View full text Add to dashboard Cite

Original article is available at : http://www.springerlink.com/ Copyright Springer [Full text of this article is not available in the UHRA]Design and performance comparison of high-order operational transconductance amplifier and capacitor (OTA-C) filters using leapfrog (LF) and inverse-follow-the-leader-feedback (IFLF) structures are investigated. The filters are designed for a 125 MHz seventh-order equiripple group delay lowpass characteristic with and without gain boost and simulated in 0.25 ??m 2-V CMOS. A fully differential highly linear OTA with cross-coupled input pairs and regulated cascode output is used for the simulation. Simulated results show that while the IFLF OTA-C filter can achieve a higher gain boost, the LF OTA-C filter has better other performances

show abstract

“…Assuming a single-tone excitation and letting be the maximum signal level at the output of the filter, the dynamic range can be expressed as DR = (1=2) 1 ( =U ) P =U state-space descriptions to evaluate noise performance through simple matrix manipulations. Similar approaches to noise evaluation have been used in [2], [3]. In this paper, we adopt these noise evaluation techniques.…”

mentioning

confidence: 99%

“…In this paper, we adopt these noise evaluation techniques. Also, we adopt the general -structure proposed in [3].…”

mentioning

confidence: 99%

“…Consequently, no systematic method is yet available to evaluate the impact of both noise and distortion on a general -filter structure, thereby limiting the ability of designers to maximize the dynamic range of practical filter implementations. This paper presents methods and techniques to evaluate the impact of both noise and distortion on the -filter structure of [3] through simple and systematic matrix algebra. For distortion evaluation we combine state-space and Volterra Series representations [10] in such a way that they can be easily embedded in matrix form.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Matrix Methods for the Dynamic Range Optimization of Continuous-Time $G_{m}$-$C$ Filters

Fernandez-Bootello¹,

Delgado‐Restituto

Rodríguez-Vázquez³

2008

IEEE Trans. Circuits Syst. I

View full text Add to dashboard Cite

Analysis and optimization of noise in continuous-time OTA-C filters

Cited by 18 publications

References 26 publications

A general framework for evaluating nonlinearity, noise and dynamic range in continuous‐time OTA‐C filters for computer‐aided design and optimization

A general framework for evaluating nonlinearity, noise and dynamic range in continuous‐time OTA‐C filters for computer‐aided design and optimization

Performance comparison of high-order IFLF and LF linear phase lowpass OTA-C filters with and without gain boost

Matrix Methods for the Dynamic Range Optimization of Continuous-Time $G_{m}$-$C$ Filters

Contact Info

Product

Resources

About