Research Article | Open Access

# The Generalization of the Poisson Sum Formula Associated with the Linear Canonical Transform

**Academic Editor:**Baolin Wang

#### Abstract

The generalization of the classical Poisson sum formula, by replacing the ordinary Fourier transform by the canonical transformation, has been derived in the linear canonical transform sense. Firstly, a new sum formula of Chirp-periodic property has been introduced, and then the relationship between this new sum and the original signal is derived. Secondly, the generalization of the classical Poisson sum formula to the linear canonical transform sense has been obtained.

#### 1. Introductions

As a generalization of the classical Fourier transform and the fractional Fourier transform (FrFT), the linear canonical transform (LCT) receives much interest in recent years [1–3]. Many important transforms, for example, the Fourier transform, the Fresnel transform, and the scaling operations are all special cases of the LCT. It has been shown to be one of the most useful tools in several areas [4–6], including optics, quantum physics, and in the signal processing community. Its relationship with the Fourier transform and the fractional Fourier transform can be found in [7, 8]. The well-known operations, for example, the Hilbert transform, the Parseval relationship, the convolution and product operations, and the spectral analysis, in traditional Fourier domain have been extended to the linear canonical transform domain by different authors [9–13]. For further properties and applications of LCT in optics and signal processing community, one can refer to [1, 2]. The classical sampling theorems associated with the LCT have also been investigated and studied in the LCT domain in various literatures. The extensions of the classical Shannon sampling theorem for band-limited or time-limited signals in the LCT domain have been deduced in [13, 14].

However, for the best of our knowledge, none of the research papers throw light on the study of the traditional Poisson sum formula [15–21] associated with the LCT have been reported as yet. The Poisson summation formula is a very useful tool not only in many branches of the mathematics, but also it finds many applications in various fields, for example, mechanics, signal processing community, and many scientific fields. It is therefore, worthwhile as well as interesting to investigate the Poisson sum formula associated with the LCT.

The objective of this paper is to study and investigate the Poisson formula associated with the LCT. In other words, we want to generalize the classical Poisson sum formula by replacing the ordinary Fourier transform by the canonical transform. In order to obtain the desired results for a signal , we first deduce a new sum formula for the signal and then achieve the innovative results in the LCT domain. The paper is organized as follows, the preliminaries are proposed in Section 2, the main results of the paper are investigated in Section 3, and the conclusion is given in Section 4.

#### 2. Preliminaries

##### 2.1. The Linear Canonical Transform

The linear canonical transform (LCT) of a signal with parameter matrix is defined as [1–3] where and , . The parameter , and satisfy det, . In this case, the linear canonical transform is a unitary transform [1], therefore we can derive the inverse transform of LCT as another LCT transform.

The inverse transform of LCT can be derived by an LCT with the parameter of as following:

The LCT can be looked at as the generalization of the well-known operations in the science and engineering community [4–6]. The relationship between the LCT and the Fourier transform, the fractional Fourier transform have been derived in [1–3].

A signal is said to be band-limited with respect to in linear canonical transform domain, when where is called the bandwidth of signal in the linear canonical transform domain. At the same time, a signal is called Chirp-periodic with period and of parameter if it satisfies the following equation:

The following identities will be used in the following sections.

Lemma 2.1. *The inverse linear canonical transform of signal for parameter is
**
And the inverse linear canonical transform of signal is
*

*Proof. *These results can be derived easily by the definition of the LCT and the inverse transform of LCT.

Assuming a signal is band-limited to in the linear canonical transform domain, then from the results derived in [13], is not band-limited in the traditional Fourier domain. Therefore, the classical results of bandlimited signal processing method in Fourier domain can be used in the LCT domain to obtain the novel results associated with the LCT.

##### 2.2. The Poisson Sum Formula

The Poisson sum formula demonstrates that the sum of infinite samples in time domain of a signal is equivalent to the sum of infinite samples of in the Fourier domain. Mathematically, the Poisson sum formula can be represented as follows: or where is the traditional Fourier transform of signal . It is well known that it will be valid only if and its Fourier transform are regular enough and only if both series of (2.9) converge [20].

In order to obtain the new results associated with the linear canonical transform, a new summation associated with the signal is introduced as following: where is a constant. From (2.10), the function can be seen as a periodic phase-shift replica of the original function . The signal will be used in the following sections to investigate the Poisson sum formula associate with the linear canonical transform.

#### 3. The Main Results

Suppose a signal is band-limited to in linear canonical transform domain of parameter , then, from (2.10) a new function can be deduced from signal . Firstly, the properties of the signal associated with the linear canonical transform can be derived from Theorem 3.1.

Theorem 3.1. *Suppose a signal is band-limited to in the linear canonical transform domain of parameter , and , then the following results about is true.*(a)* is a Chirp-periodic signal with period .*(b)* is a band-limited signal in linear canonical transform domain with parameter , if and only if has a finite number of nonzero linear canonical series coefficients for any .*

*Proof. *(a) By the definition of the Chirp-periodicity, we obtain
This proves the Chirp-periodicity of the signal .

(b) To prove the necessary condition, the th coefficient of signal can be deduced from the linear canonical series definition proposed in [4] as
Equation (3.2) can be rewritten as
Since is a band-limited signal in linear canonical transform domain of parameter , that is to say
Comparing (3.3) and (3.4), we obtain
Therefore, the necessary condition is proved.

To prove the sufficient condition, let us assume that for , where is any finite integer. From (3.5), the
Hence, is band-limited signal having bandwidth as following:
This proves the sufficient condition of the theorem.

Based on the derived results of Theorem 3.1, the following Theorem 3.2 can be deduced.

Theorem 3.2. *Suppose a signal is band-limited to in the linear canonical transform domain of parameter , and is derived by shifting signal to left and right, then the following conclusions can be deduced.*(a)*When , can be deduced from the following formula:
*(b)*When , can be deduced from the following formula:
*(c)*When , can be deduced from the following formula:
*

*Proof. **Proof of (a)*. Since is a band-limited signal in the linear canonical transform domain, if sampled in the linear canonical transform domain of order at a rate of , then the samples can be represented as follows:
The first part of (3.11) can be reorganized as
If we let , then (3.12) can be rewritten as
Applying the convolution and product theorem proposed in [7] and Lemma 2.1 to (3.13), the inverse linear canonical transform of formula (3.13) can be represented as
From the second part of (3.11), the inverse linear canonical transform of can be derived as
If we select , then from (3.14)-(3.15)
This proves (a).*Proof of (b)*. Similar to the method of proving (a), if is sampled in the linear canonical transform domain of parameter at a rate of , there are essentially three nonzero samples of :
In this condition, (3.14) is also correct, and from (3.13), the relationship between and can be derived as follows:
While can be deduced from (3.18) and Lemma 2.1 as
If is chosen, then from (3.18)-(3.19).
Thus, (b) is also proved.

*Proof of (c)*. If is sampled in linear canonical transform domain of order at a rate of , there are essentially nonzero samples remaining
Again, (3.14) is also correct in this case, and using similar method in proving (a) and (b), can be deduced as
If we select , then
Part (c) of Theorem 3.1 is proved.

#### 4. Conclusion

In this paper, the generalization of the classical Poisson sum formula to the linear canonical transform domain is investigated, by replacing the ordinary Fourier transform by the canonical transform, we firstly derived a new Chirp-periodic sum, and then the classical Poisson summations are generalized to the linear canonical transform domain based on the relationship derived. The classical results can be looked at as the special cases of the derived results. The applications of the derived results in sampling theories, signal analysis will be investigated in the linear canonical transform domain in the future.

#### Acknowledgments

This work is supported by National Natural Science Foundations of China (no. 60901058 and no. 61171195) and the Beijing Natural Science Foundation (no.1102029).

#### References

- R. Tao, B. Deng, and Y. Wang,
*Fractional Fourier Transform and Its Applications*, Tsinghua University Press, Beijing, China, 2009. - M. Zhu, B.-Z. Li, and G.-F. Yan, “Aliased polyphase sampling associated with the linear canonical transform,”
*IET Signal Processing*, vol. 6, no. 6, pp. 594–599, 2012. View at: Publisher Site | Google Scholar - K. B. Wolf,
*Integral Transforms in Science and Engineering*, vol. 11 of*Mathematical Concepts and Methods in Science and Engineering*, Plenum Press, New York, NY, USA, 1979. View at: Zentralblatt MATH - C.-P. Li, B.-Z. Li, and T.-Z. Xu, “Approximating bandlimited signals associated with the LCT domain from nonuniform samples at unknown locations,”
*Signal Processing*, vol. 92, no. 7, pp. 1658–1664, 2012. View at: Publisher Site | Google Scholar - D. Wei, Q. Ran, and Y. Li, “Reconstruction of band-limited signals from multichannel and periodic nonuniform samples in the linear canonical transform domain,”
*Optics Communications*, vol. 284, no. 19, pp. 4307–4315, 2011. View at: Publisher Site | Google Scholar - W. Qiu, B.-Z. Li, and X.-W. Li, “Speech recovery based on the linear canonical transform,”
*Speech Communication*, vol. 50, no. 1, pp. 40–50, 2013. View at: Google Scholar - B. Deng, R. Tao, and Y. Wang, “Convolution theorems for the linear canonical transform and their applications,”
*Science in China. Series F. Information Sciences*, vol. 49, no. 5, pp. 592–603, 2006. View at: Publisher Site | Google Scholar - S.-C. Pei and J.-J. Ding, “Relations between fractional operations and time-frequency distributions, and their applications,”
*IEEE Transactions on Signal Processing*, vol. 49, no. 8, pp. 1638–1655, 2001. View at: Publisher Site | Google Scholar - B.-Z. Li and T.-Z. Xu, “Spectral analysis of sampled signals in the linear canonical transform domain,”
*Mathematical Problems in Engineering*, vol. 2012, Article ID 536464, 19 pages, 2012. View at: Publisher Site | Google Scholar - B.-Z. Li, R. Tao, T.-Z. Xu, and Y. Wang, “The Poisson sum formulae associated with the fractional Fourier transform,”
*Signal Processing*, vol. 89, no. 5, pp. 851–856, 2009. View at: Publisher Site | Google Scholar - K. K. Sharma and S. D. Joshi, “Signal separation using linear canonical and fractional Fourier transforms,”
*Optics Communications*, vol. 265, no. 2, pp. 454–460, 2006. View at: Publisher Site | Google Scholar - R. Tao, B.-Z. Li, Y. Wang, and G. K. Aggrey, “On sampling of band-limited signals associated with the linear canonical transform,”
*IEEE Transactions on Signal Processing*, vol. 56, no. 11, pp. 5454–5464, 2008. View at: Publisher Site | Google Scholar - B.-Z. Li, R. Tao, and Y. Wang, “New sampling formulae related to linear canonical transform,”
*Signal Processing*, vol. 87, no. 5, pp. 983–990, 2007. View at: Publisher Site | Google Scholar - J. J. Healy and J. T. Sheridan, “Sampling and discretization of the linear canonical transform,”
*Signal Processing*, vol. 89, no. 4, pp. 641–648, 2009. View at: Publisher Site | Google Scholar - H. G. Feichtinger, “Parseval's relationship for nonuniform samples of signals with several variables,”
*IEEE Transactions on Signal Processing*, vol. 40, no. 5, pp. 1262–1263, 1992. View at: Publisher Site | Google Scholar - F. Marvasi, “Reflections on the Poisson sum formula and the uniform sampling,”
*IEICE Transactions*, vol. e67, no. 9, pp. 494–501. View at: Google Scholar - A. Córdoba, “La formule sommatoire de Poisson,”
*Comptes Rendus des Séances de l'Académie des Sciences. Série I. Mathématique*, vol. 306, no. 8, pp. 373–376, 1988. View at: Google Scholar - A. Córdoba, “Dirac combs,”
*Letters in Mathematical Physics*, vol. 17, no. 3, pp. 191–196, 1989. View at: Publisher Site | Google Scholar | Zentralblatt MATH - J.-P. Kahane and P.-G. Lemarié-Rieusset, “Remarques sur la formule sommatoire de Poisson,”
*Studia Mathematica*, vol. 109, no. 3, pp. 303–316, 1994. View at: Google Scholar | Zentralblatt MATH - A. L. Durán, R. Estrada, and R. P. Kanwal, “Extensions of the Poisson summation formula,”
*Journal of Mathematical Analysis and Applications*, vol. 218, no. 2, pp. 581–606, 1998. View at: Publisher Site | Google Scholar | Zentralblatt MATH - K. Gröchenig, “An uncertainty principle related to the Poisson summation formula,”
*Studia Mathematica*, vol. 121, no. 1, pp. 87–104, 1996. View at: Google Scholar | Zentralblatt MATH

#### Copyright

Copyright © 2012 Jun-Fang Zhang and Shou-Ping Hou. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.