U.S. patent number 3,851,162 [Application Number 05/352,382] was granted by the patent office on 1974-11-26 for continuous fourier transform method and apparatus.
This patent grant is currently assigned to The United States of America as represented by the Administration of the. Invention is credited to Robert M. Munoz.
United States Patent |
3,851,162 |
Munoz |
November 26, 1974 |
CONTINUOUS FOURIER TRANSFORM METHOD AND APPARATUS
Abstract
An input analog signal to be frequency analyzed is separated
into N number of simultaneous analog signal components each
identical to the original but delayed relative to the original by a
successively larger time delay. The separated and delayed analog
components are combined together in a suitable number of adders and
attenuators in accordance with at least one component product of
the continuous Fourier transform and analog signal matrices to
separate the analog input signal into at least one of its
continuous analog frequency components of bandwidth 1/N times the
bandwidth of the original input signal. Given the separated
frequency components, the original analog input signal can be
reconstituted by combining the separate analog frequency components
in accordance with the component products of the continuous Fourier
transform and analog frequency component matrices. The continuous
Fourier transformation is useful for spectrum analysis, filtering,
transfer function synthesis, and communications.
Inventors: |
Munoz; Robert M. (Los Altos,
CA) |
Assignee: |
The United States of America as
represented by the Administration of the (Washington,
DC)
|
Family
ID: |
23384911 |
Appl.
No.: |
05/352,382 |
Filed: |
April 18, 1973 |
Current U.S.
Class: |
708/821;
324/76.21; 324/76.35; 702/77 |
Current CPC
Class: |
G06G
7/1921 (20130101); H04B 1/66 (20130101); H04B
3/141 (20130101) |
Current International
Class: |
G06G
7/00 (20060101); H04B 1/66 (20060101); H04B
3/04 (20060101); G06G 7/19 (20060101); H04B
3/14 (20060101); G06f 015/34 () |
Field of
Search: |
;235/156,152,184,181,197 |
References Cited
[Referenced By]
U.S. Patent Documents
Primary Examiner: Gruber; Felix D.
Assistant Examiner: Gottman; James F.
Attorney, Agent or Firm: Morin; Armand G. Brekke; Darrell G.
Manning; John R.
Claims
What is claimed is:
1. In a method for continuous analog analysis for a time varying
input function f(t) in the time domain into at least one of its
Fourier Frequency components C.sub.m (t) the steps of:
continuously producing N signal components f.sub.m (t)/N ranging
from f.sub.0 (t)/N to f.sub.N.sub.-1 (t)/N wherein each signal
component except f.sub.0 (t)/N is delayed an amount T from the
previous signal component;
continuously combining separated ones of said signal components
[f.sub.m (t)] f.sub.m (t)/N together so as to produce at least one
continuous output function C.sub.m (t) corresponding to one of the
Fourier frequency components of the time varying input function
f(t) to be frequency analyzed.
2. The method of claim 1 wherein the step of combining said
separated components f.sub.m (t)/N together so as to produce at
least one output function C.sub.m (t) corresponding to one of the
Fourier frequency components of the time varying input signal f(t)
comprises the step of, combining the time delayed continuous signal
components f.sub.m (t)/N together according to at least one of the
component products of the matrix product: DF(t) where D is the
discrete Fourier transform matrix and F(t) is the delayed input
signal component matrix.
3. The method of claim 2 wherein the step of combining the delayed
signal components f.sub.m (t)/N according to at least one component
product of the matrix product includes the step of, adding the
delayed signal components f.sub.m (t)/N according to at least one
of the component products of said matrix product.
4. The method of claim 2 wherein D is defined by the matrix:
5. The method of claim 1 wherein N is a power of 2.
6. The method for reconstituting a time varying function f(t) in
the time domain from a plurality of N number of its continuously
time varying C.sub.m (t) Fourier frequency components in the
frequency domain the steps of:
continuously combining the separate Fourier frequency components
C.sub.m (t) according to the product of the matrix equation
f(t) = DC(t)
where D is the discrete Fourier transform matrix and C(t) is the
matrix for the continuous separate Fourier frequency
components.
7. The method of claim 6 wherein the step of combining a plurality
of the continuous time varying Fourier frequency components C.sub.m
(t) together so as to reconstitute the original time varying
function f(t) includes, combining the separate Fourier frequency
components C.sub.m (t) according to the product of the matrix
Equation:
f(t) = DC(t)
where D is the discrete Fourier transform matrix and C(t) is the
matrix for the continuous separate Fourier frequency
components.
8. The method of claim 7 wherein the D matrix is defined by the
matrix equation:
9. The method of claim 8 where
10. In an analog apparatus for continuous frequency analysis of a
time varying input function f(t) in the time domain into at least
one of its Fourier frequency components C.sub.m (t):
means for continuously generating N signal components
f.sub.m (t)/N ranging from f.sub.0 (t)/N to f.sub.N.sub.-1 (t)/N
wherein each signal component except f.sub.0 (t)/N is delayed an
amount T from the previous signal component;
means for continuously combining said signal components f.sub.m
(t)/N together so as to produce at least one continuous output
function C.sub.m (t) corresponding to one of the Fourier frequency
components of the time varying input function f(t) to be frequency
analyzed.
11. The analog apparatus of claim 10 wherein the means for
combining said separated signal components f.sub.m (t)/N together
so as to produce at least one output function C.sub.m (t)
corresponding to one of the Fourier frequency components of the
time varying input signal f(t) includes, means for combining the
time delayed continuous signal components f.sub.m (t)/N according
to at least one of the component products of the matrix
product:
DF(t)
where D is the discrete Fourier transform matrix and F(t) is the
separated input signal component matrix.
12. The analog apparatus of claim 11 wherein said means for
combining the delayed signal components according to at least one
component product of the matrix product includes, means for adding
the delayed signal components according to at least one of the
component products of said matrix product.
13. The analog apparatus of claim 11 where D is defined by the
matrix:
14. The analog apparatus of claim 10 wherein N is a power of 2.
15. Apparatus comprising:
first analog means for continuously producing N time varying
Fourier frequency components C.sub.m (t) in the frequency domain of
a time varying function f(t) in the time domain;
said first analog means comprising: means for continuously
generating N signal components f.sub.m (t)/N ranging from f.sub.0
(t)/N to f.sub.N.sub.-1 (t)/N wherein each signal component except
f.sub.0 (t)/N is delayed an amount T from the previous signal
component; and means for continuously combining said signal
components f.sub.m (t)/N together so as to produce N varying
Fourier frequency components C.sub.m (t);
channel means for conveying each time varying Fourier frequency
component to an inverse Fourier transformer, said transformer
comprising second analog means for combining the continuously time
varying Fourier components C.sub.m (t) together so as to
reconstitute the original time varying function f(t).
16. The apparatus of claim 15 wherein said means for combining a
plurality of the continuously time varying frequency components
C.sub.m (t) together so as to reconstitute the original time
varying function f(t) includes, means for combining the separate
frequency components C.sub.m (t) according to the component
products of the matrix product
DC(t)
where D is the discrete Fourier transform matrix and C(t) is the
matrix for the continuous separate Fourier frequency
components.
17. The apparatus of claim 16 wherein:
18. The apparatus of claim 17 wherein:
19. In an analog apparatus for continuous frequency analysis of a
time varying input function f(t) in the time domain into at least
one of its Fourier frequency components C.sub.m (t):
means for continuously generating N signal components f.sub.m (t)/N
ranging from f.sub.0 (t)/N to f.sub.N.sub.-1 (t)/N wherein each
signal component except f.sub.0 (t)/N is delayed an amount T from
the previous signal component;
said generating means including a tape recorder with a recording
head and (N-2) staggered playback heads, said signal component
f.sub.0 (t)/N being connected to said recording head and each of
the remaining signal components being produced at one of said
playback heads;
means for continuously combining said signal components f.sub.m
(t)/N together so as to produce at least one continuous output
function C.sub.m (t) corresponding to one of the Fourier frequency
components of the time varying input function f(t) to be frequency
analyzed.
20. An analog apparatus as set forth in claim 19 wherein said means
for continuously combining signal components consists of a network
of operational amplifiers.
21. Apparatus comprising:
first analog means for continuously producing N time varying
Fourier frequency components C.sub.m (t) in the frequency domain of
a time varying function f(t) in the time domain;
said first analog means comprising: means for continuously
generating N signal components f.sub.m (t)/N ranging from f.sub.0
(t)/N to f.sub.N.sub.-1 (t)/N wherein each signal except f.sub.0
(t)/N is delayed an amount T from the previous signal component;
and means for continuously combining said signal components f.sub.m
(t)/N together so as to produce N varying Fourier frequency
components C.sub.m (t);
Said generating means including a tape recorder with a recording
head and (N-2) staggered playback heads, said signal component
f.sub.0 (t)/N being connected to said recording head and each of
the remaining signal components being produced at one of said
playback heads;
channel means for conveying each time varying Fourier frequency
component to an inverse Fourier transformer, said transformer
comprising second analog means for combining the continuously time
varying Fourier components C.sub.m (t) together so as to
reconstitute the original time varying function f(t);
said combining means consisting of a network of operational
amplifiers.
22. Apparatus as set forth in claim 21 wherein said inverse Fourier
transformer consists of a network of operational amplifiers and
attenuators.
Description
The invention described herein was made by an employee of the
United States Government and may be manufactured and used by or for
the Government for governmental purposes without the payment of any
royalties thereon or therefor.
BACKGROUND OF THE INVENTION
The present invention relates in general to method and apparatus
for performing Fourier transformations and more particularly to an
improved continuous Fourier transformation and systems using
same.
DESCRIPTION OF THE PRIOR ART
Heretofore, analog input signals have been analyzed by sampling the
analog input signal at a multiplicity of time displaced intervals,
converting such sampled data to discrete digital form in an analog
to digital converter and performing a discrete Fourier
transformation, typically by the fast Fourier transform method, to
convert the signal data in the time domain into its corresponding
discrete frequency components in the frequency domain, thereby
obtaining a discrete spectral representation of the input signal to
be analyzed.
I is also known from the prior art that once an analog signal has
been separated into its corresponding discrete Fourier components
in the frequency domain that a discrete representation of the
original analog signal can be reconstituted by performing an
inverse Fourier transformation on the discrete spectral Fourier
components in a digital computer to derive a discrete
representation of the original analog signal in the time domain.
The discrete fast Fourier transform method and apparatus is
disclosed in an article "What is the Fast Fourier Transform?,"
appearing in the I.E.E.E. Transactions on Audio and
Electroacoustics, volume AU-15, No. 2, of June 1967, pages
45-55.
One of the problems with the discrete Fourier transform is that it
requires the use of a digital computer with associated
analog-to-digital converters and the analysis performed by the
computer comprises many complex multiplications, additions, and
memory cycles.
SUMMARY OF THE PRESENT INVENTION
The principal object of the present invention is the provision of
an improved Fourier transform method and apparatus and more
particularly of a simplified continuous Fourier transform method
which does not require a complex digital computer for
implementation.
In one feature of the present invention, an analog signal to be
analyzed is separated into N number of analog components each
delayed relative to the original signal or the reference one of
said signal components by a successively larger time delay, such
reference and delayed components are added together in accordance
with at least one of the component products of the fast Fourier
matrix (D matrix) and the delayed input signal component matrix
F(t) to produce at least one continuous output function C.sub.m (t)
corresponding to one of the frequency components of the analog
input signal to be analyzed.
In another feature of the present invention, the Fourier components
in the frequency domain of an original analog signal are combined
in accordance with the component product of the discrete Fourier
transform matrix (D matrix) and the Fourier components matrix
(C.sub.m (t) matrix) to reconstitute the original analog input
signal.
In another feature of the present invention, an analog input signal
having a certain bandwidth is Fourier transformed into N number of
Fourier frequency components each component having 1/N .times. the
bandwidth of the original input signal. Such separate Fourier
frequency components are transmitted simultaneously over N number
of different channels to a receiver. The received Fourier
components are recombined in accordance with the inverse Fourier
transform to reconstitute the original input signal, whereby a
relatively wide bandwidth signal is transmitted over N number of
relatively narrow band individual channels.
Other features and advantages of the present invention will become
apparent upon a perusal of the following specification taken in
connection with the accompanying drawings wherein:
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a signal flow graph depicting the continuous Fourier
transformation of a complex (two-wire) analog input signal into
four separate complex Fourier frequency components,
FIG. 2 is a signal flow graph depicting the continuous Fourier
transformation of a real (one-wire) input signal to its respective
Fourier frequency components,
FIG. 3 is a physical implementation of the system of FIG. 2,
FIG. 4 is an alternative physical implementation of the input
portion of the circuit of FIG. 3 and delineated by line 4--4,
FIG. 5 is a plot of the input signal to be Fourier analyzed and the
output Fourier components as a function of time and depicting the
discrete Fourier transform output indicated by the dots
superimposed upon the continuous Fourier transform output,
FIG. 6 is a schematic circuit diagram for a physical implementation
of a continuous Fourier transform circuit similar to that of FIG. 3
except for eight time delayed input components,
FIG. 7 is a composite plot of band limited input signal data,
frequency bands of the separate Fourier components, and the
frequency response of the first Fourier frequency output
coefficient C.sub.0, all as a function of frequency,
FIG. 8 is a schematic block diagram of a data transmission system
incorporating features of the present invention,
FIG. 9 is a diagram similar to that of FIG. 8 for modifying an
input signal, and
FIG. 10 is a schematic circuit diagram of an inverse continuous
Fourier transform apparatus.
DESCRIPTION OF THE PREFERRED EMBODIMENTS
The prior method of discrete Fourier transform will first be
described followed by a description of an extension thereof under
the present invention to a continuous Fourier transform method and
apparatus. In the discrete Fourier transform method, a band limited
continuous complex function of time f(t) is considered to contain a
maximum frequency component .omega..sub.s /2 wherein .omega..sub.s
is the rate at which the function f(t) is to be sampled to produce
a sampled data function f*(nT), where T = 1/.omega..sub.s seconds.
A set of N sequentially ordered magnitudes of f*(nT) where n = 0,
1, . . . , N - 1, is selected and the discrete Fourier transform of
this set is as follows: ##SPC1##
where
j = .sqroot.-1
m = 0, 1, . . . N-1
and c.sub.m are the N complex frequencies coefficients.
The inverse operation of computing the original data set from the
coefficients is given as follows: ##SPC2##
where n = 0, 1, . . . , N-1
These equations can be written in matrix form in the following
way:
C = 1/N D F Eq. (3)
and
F = D C Eq. (4)
where C = c.sub.0 1 1 1 1 c.sub.1 1 e.sup.j e.sup.2j
e.sup.(N.sup.-1) j e.sup.2j e.sup.4j e.sup.2(N.sup.-1)j
c.sub.N.sub.-1 D = 1 e.sup.(N.sup.-1)j e.sup.2(N.sup.-1)j
e.sup.(N.sup.-1)2j and F = f* (o) f* (T) f ((N-1) T)
The discrete fast Fourier transform is obtained for Equations (3)
and (4) by recognizing and using the properties of the D matrix to
simplify the computations. Since all entries in the D matrix are
periodic roots of unity, and symmetric about the main diagonal, a
great simplification is possible where N is a power of 2. The
highest degree of symmetry and hence the greatest simplification is
permitted when N fulfills this requirement. The matrix equations of
(3) and (4) are typically solved with a digital computer programmed
to perform the fast Fourier transform. The program involves many
complex multiplications and additions. Although the computations
are relatively complex the fast Fourier transform is relatively
efficient because using the fast Fourier transform 2N log N complex
multiply operations plus the attendant addition and memory cycles
are required, whereas a straight implementation of the matrix
equations (3) and (4) would require approximately N.sup.2 complex
multiply operations and the fast Fourier transform reduces this by
a factor of 2 log N/N which is appreciable for large N.
In the continuous transform method of the present invention, the
discrete Fourier transform equations (3) and (4) are utilized and
the input signal f(t) is considered as a vector quantity having
real and imaginary components. Because Equations (3) and (4) are
independent of time, the independent variable F can be made a
function of time F(t) to produce the following continuous Fourier
transform:
C(t) = 1/N DF(t). Eq. (5)
Matrix Equation (5) may be expanded and written as follows:
C.sub.0 (t) 1 1 1 1 f.sub.0 (t) C.sub.1 (t) 1 e.sup.j e.sup.2j
e.sup.(N.sup.-1)j f.sub.1 (t) C.sub.2 (t) 1 e.sup.2j e.sup.4
e.sup.2(N.sup.-1)j f.sub.2 (t) =1/N Eq. (6) C.sub.N.sub.-1 (t) 1
e.sup.(N.sup.-1)j e.sup.2(N.sup.-1)j e.sup.(N.sup.-1)2j
f.sub.(N.sub.-1) (t)
where
f(t) = f(t-jT)
As in the fast Fourier transform a considerable simplification in
the computation is achieved if N is selected to be a binary number,
i.e., a power of 2 such as 2, 4, 8, 16, etc. This simplifies F and
greatly reduces the complexity. The matrix Equation (6), when
solved for the complex frequency coefficients C.sub.m (t), produces
a set of equations as follows:
C.sub.0 (t) = 1/N[f.sub.0 (t)+f.sub.1 (t) +f.sub.2 (t)
f.sub.N.sub.-1 (t)] (7) C.sub.1 (t) = 1/N[f.sub.0 (t)+e.sup.j
f.sub.1 (t) -f.sub.2 (t) e.sup.(N.sup.-1)j f.sub.N.sub.-1 (t)] (8)
C.sub.2 (t) = 1/N[f.sub.0 (t)-f.sub.1 (t) +f.sub.2 (t)
e.sup.2(N.sup.-1)j f.sub.N.sub.-1 (t)] (9) C.sub.N.sub.-1 (t)=
1/N[f.sub.0 (t)+e.sup.(N.sup.-1)j f.sub.1 (t)+e.sup.2( N.sup.-1)j
f.sub.2 (t) e.sup.(N.sup.- 1)2j f.sub.N.sub.-1 (t)] (10)
For N = 4, these equations reduced to:
C.sub.0 (t) = 1/N [f.sub.0 (t) + f.sub.1 (t) + f.sub.2 (t) +
f.sub.3 (t)] Eq. (11)
C.sub.1 (t) = 1/N [f.sub.0 (t) + e.sup.j f.sub.1 (t) - f.sub.2 (t)
- e.sup.j f.sub.3 (t)] Eq. (12)
C.sub.2 (t) = 1/N [f.sub.0 (t) - f.sub.1 (t) + f.sub.2 (t) -
f.sub.3 (t)] Eq. (13)
C.sub.3 (t) = 1/N [f.sub.0 (t) - e.sup.j f.sub.1 (t) - f.sub.2 (t)
+ e.sup.j f.sub.3 (t)] Eq. (14)
The signal flow graph for Equations 11-14 is illustrated in FIG. 1.
In the signal flow graph, each node represents a variable, and the
arrows terminating at that node originate at the nodes whose
variables contribute to the value of the variable at that node. The
contributions are additive, and the weight of each contribution, if
other than unity, is indicated by the constant written close to the
arrowhead of the transmission. Equations 11-14 are separated into
real and imaginary components as follows:
ReC.sub.0 (t) = 1/N [Ref.sub.0 (t) + Ref.sub.1 (t) + Ref.sub.2 (t)
+ Ref.sub.3 (t)] Eq. (15)
ImC.sub.0 (t) = 1/N [Imf.sub.0 (t) + Imf.sub.1 (t) + Imf.sub.2 (t)
+ Imf.sub.3 (t)] Eq. (16)
ReC.sub.1 (t) = 1/N [Ref.sub.0 (t) - Imf.sub.1 (t) - Ref.sub.2 (t)
+ Imf.sub.3 (t)] Eq. (17)
ImC.sub.1 (t) = 1/N [Imf.sub.0 (t) + Ref.sub.1 (t) - Imf.sub.2 (t)
- Ref.sub.3 (t)] Eq. (18)
ReC.sub.2 (t) = 1/N [Ref.sub.0 (t) - Ref.sub.1 (t) + Ref.sub.2 (t)
- Ref.sub.3 (t)] Eq. (19)
ImC.sub.2 (t) = 1/N [Imf.sub.0 (t) - Imf.sub.1 (t) + Imf.sub.2 (t)
- Imf.sub.3 (t)] Eq. (20)
ReC.sub.3 (t) = 1/N [Ref.sub.0 (t) + Imf.sub.1 (t) - Ref.sub.2 (t)
- Imf.sub.3 (t)] Eq. (21)
ImC.sub.3 (t) = 1/N [Imf.sub.0 (t) - Ref.sub.1 (t) - Imf.sub.2 (t)
+ Ref.sub.3 (t)] Eq. (22)
Equations 15-22 could be implemented with hardware, however,
considering a one dimensional input signal having only a real and
no imaginary component, Equations 15-22 are greatly simplified by
recognizing that:
Imf.sub.0 (t) = Imf.sub.1 (t) = Imf.sub.2 (t) = Imf.sub.3 (t) =
0
Thus:
ReC.sub.0 (t) = 1/N [Ref.sub.0 (t) + Ref.sub.1 (t) + Ref.sub.2 (t)
+ Ref.sub.3 (t)] Eq. (23) ImC.sub.0 (t) = 0 Eq. (24)
ReC.sub.1 (t) = ReC.sub.3 (t) = 1/N [Ref.sub.0 (t) - Ref.sub.2 (t)]
Eq. (25)
ImC.sub.1 (t) = -ImC.sub.3 (t) = 1/N [Ref.sub.1 (t) - Ref.sub.3
(t)] Eq. (26)
ReC.sub.2 (t) = 1/N [Ref.sub.0 (t) - Ref.sub.1 (t) + Ref.sub.2 (t)
- Ref.sub.3 (t)] Eq. (27) ImC.sub.2 (t) = 0 Eq. (28)
ReC.sub.3 (t) - 1/N [Ref.sub.0 (t) - Ref.sub.2 (t)] Eq. (29)
ImC.sub.3 (t) = 1/N [- Ref.sub.1 (t) + Ref.sub.3 (t)] Eq. (30)
Since ImC.sub.0 (t) and ImC.sub.2 (t) = zero, no hardware
implementation for Fourier frequency components is necessary or
possible. Therefore, equations 23-30 reduced to only four
independent equations, namely Equations 13, 25, 26 and 27, the
signal flow graph for which is depicted in FIG. 2. In the
continuous transform, f.sub.0 (t) is identical to the reference
input signal f(t) and f.sub.1 (t) is identified with f.sub.0 (t+T),
f.sub.2 (t) is identified with f.sub.0 (t+2T) and f.sub.3 (t) is
identified with f.sub.0 (t+3T).
The signal flow graph of FIG. 2 is implemented with hardware as
shown in FIG. 3 to provide a continuous Fourier transform
apparatus. More particularly, the input function of time f(t)
(magnitude) is first divided by N in attenuator 11 to provide a
first reference input signal f.sub.0 (t)/N. 1/N is a scaling
constant equal to the reciprocal of the number of Fourier frequency
components. A sample of the output of the attenuator 11 is fed to a
first delay 12 to be delayed by a time T. The output of the delay
12 forms the second input signal, namely f.sub.1 (t)/N. A sample of
the output of delay 12 is fed to a second delay 13 which delays the
signal passing therethrough by the same time T such that the output
of the second delay 13 forms the third input signal, namely f.sub.2
(t)/N. An output of the second delay 13 is fed to a third delay 14
for delaying the fourth signal by a time T relative to the third
signal to produce the fourth input reference signals namely f.sub.3
(t)N. The continuous input signals are combined in the inverting
operational amplifiers 15 in accordance with the signal flow graph
of FIG. 2 to produce the four outputs, namely, ReC.sub.0 (t),
ReC.sub.2 (t), ReC.sub.1 (t) = ReC.sub.3 (t), ImC.sub.1 (t) =
-ImC.sub.3 (t).
One relatively simple apparatus for deriving the time delayed input
signals for the input to the circuit of FIG. 3 is as shown in FIG.
4. More particularly, the input signal f(t) to be Fourier analyzed
is recorded on a magnetic recording tape 16. The magnetic recording
tape 16 is drawn from a supply reel 17 onto a take-up reel 18
across a number of pick-up heads 19 each head 19 being equally
spaced from the adjacent head in the direction of movement of the
recording tape 16. The outputs from each of the downstream heads 19
is successively delayed by a successively larger time compared to
the output of the upstream head or reference head. The respective
output signals are indicated above each of the respective
heads.
Referring now to FIG. 5, there is shown the signal to be analyzed
f(t) and its Fourier frequency components for N = 4 and
corresponding to the four outputs of the circuit of FIG. 3. In FIG.
5, f(t) is shown being separated into N = 4 components and sampled
four times per time window where the time window No. 1 is defined
as 0 to 4T. The information contained in the four components
ReC.sub.0 (t), ReC.sub.2 (t), ReC.sub.1 (t) and ImC.sub.1 (t) is no
greater nor less than that contained in the four original samples
because the continuous Fourier transform process is conservative,
that is, it permits information neither to be created nor
destroyed. Since only one unique set of Fourier frequency
components per window is allowed to characterize f(t), according to
the sampling theorem, each Fourier frequency component must then
contain only 1/N .times. the bandwidth limit of f(t ) or a maximum
frequency content of .omega..sub.s /2N = .omega..sub.s /8 Hz. This
accounts for the bandwidth reduction in the discrete or sampled
data case and this has a direct and immediate implication for the
continuous transform mechanism.
The continuous transform method is related to the series of
discrete Fourier transforms in successive time windows 1, 2, . . .
p and at the limit of this process, i.e., when p goes to infinity
and T goes to zero, the bandwidth relationships are invariant for
both p and T. Therefore, they obtain in the limit and apply equally
well for the continuous transform case, i.e., the bandwidth of any
Fourier component C.sub.i (t) = 1/N bandlimit of f(t).
The continuous Fourier transform mechanism of the present invention
is suited to many practical applications including filtering,
spectral analysis, and transfer function modification in the
frequency or time domain. In short, it can do all that the theory
permits of any Fourier transform mechanism and for some
applications it results in very simple and inexpensive
hardware.
Referring now to FIG. 6 there is shown a Fourier transform circuit
similar to that of FIG. 3 where N = 8. As can be seen in FIG. 6,
the hardware implementation involves merely attenuators and
amplifiers as contrasted with the prior art discrete Fourier
transform mechanism that requires complex multiplication, addition
and memory cycles. The frequency characteristics of the continuous
transform mechanism for the circuit of FIG. 6 is shown in FIG. 7
where N = 8 and Imf(t) = 0. The information band of f(t) from zero
to .omega..sub.s /2, is separated into five equibandwidth parts by
the output frequency components C.sub.0 through C.sub.4 as
indicated by frequency bands 0 through 4. This operation of
producing Fourier frequency components on a continuous basis is
identical to the operation of filtering with the added advantage
that an exact measurement of the phase of the incoming signal with
respect to .omega..sub.s is possible for each band. It can be seen
that the C.sub.0 component acts as a low pass filter and C.sub.1
acts as a bandpass filter, etc., each band having a bandwidth of
(+).omega..sub.s /2N around their respective center frequencies of
m.omega..sub.s /N where m = 0, 1 . . . . (N-1). All this filtering
action takes place simultaneously and continuously and therefore
constitutes a parallel set of N/2 filters or a spectrum analyzer.
If only one filter is needed, then the hardware can be simplified
greatly.
At frequencies above .omega..sub.s /2 the action of filtering,
unlike that of ordinary filters, repeats itself in a cyclical
manner as indicated by the frequency band containing the same
number designation in FIG. 7. This was the reason for band limiting
the input signal f(t) to avoid signal aliasing and the consequent
confusion of data that results. However, for some applications this
action may be desirable for use in a periodic filter as, for
example, in the magnetic amplifier or flux gate magnetometer where
the output signals are contained in all even harmonics of the drive
signal and it is necessary to reject the odd harmonics and
extraneous noises in other bands.
Many types of periodic filters are possible such as even and odd
harmonics as well as third, fifth, eleventh, thirteenth, nineteenth
. . . harmonic types, each selected as combinations of frequency
bands containing in the same band number or numbers. This action
can, of course, be accomplished simultaneously for different
combinations and may be useful for human speech and music signal
analysis.
Returning now to band limited information input signals, the
continuous transform mechanism can be used to make a communication
system capable of sending high bandwidth information over a
plurality of N low bandwidth lines or channels. Such a transmission
system is shown in FIG. 8. In FIG. 8, the input signal f(t) is
continuously Fourier transformed in Fourier transformer 21 in a
manner as previously described with regard to FIG. 3. The output of
transform mechanism 21 is N frequency components with the attendent
bandwidth reduction of 1/N for each of such Fourier frequency
components. The components are then transmitted over separate
channels 1 through N to be reconstituted at the receiving end via
an inverse continuous transform mechanism 22 into a facsimile of
the original signal.
Referring now to FIG. 9 there is shown an apparatus 23 adapted for
transfer function modification in the frequency domain. More
particularly, the system is similar to that of FIG. 8 with the
exception that variable attenuators 24 are placed in each of the
respective channels between the continuous Fourier transform
mechanism 21 and the inverse continuous Fourier transform mechanism
22 for modifying the frequency components in the frequency domain.
The reconstituted modified output signal G(t) appears at the output
across a load resistor 25. Convolutions in frequency or time can be
performed by using two continuous transform systems of the type
shown in FIG. 9 and multiplying the input signals or the frequency
components respectively and reconstituting or transforming these
products using another transform mechanism.
Once an input signal in the time domain has been separated into its
continuous fast Fourier transform components Cm(t) in the frequency
domain these components can be recombined to form the original
signal f(t) by means of the inverse Fourier transform, the discrete
version of which is shown in Eq. (4). In the continuous Fourier
transform, Equation (4) is rewritten as:
F(t) = D C (t) Eq. (31)
Equation (31) is solved for f.sub.0 (t) = f(t) and for N = 4 as
follows:
f.sub.0 (t) f(t) 1 1 1 1 C.sub.0 (t) f.sub.1 (t) f(t-T) 1 e.sup.j
e.sup.2j e.sup.3j C.sub.1 (t) = = Eq. (32) f.sub.2 (t) f(t-2T) 1
e.sup.2j e.sup.4j e.sup.6j C.sub.2 (t) f.sub.3 (t) f(t-3T) 1
e.sup.3j e.sup.6j e.sup.9j C.sub.3 (t)
From Equation (32):
f(t) = C.sub.0 (t) + C.sub.1 (t) + C.sub.2 (4) + C.sub.3 (t) Eq.
(33)
Taking into account real and imaginary components,
f(t) = ReC.sub.0 (t) + ImC.sub.0 (t) + ReC.sub.1 (t) + ImC.sub.1
(t) + ReC.sub.2 (t) + ImR.sub.2 (t) + ReC.sub.3 (t) + ImR.sub.3 (t)
Eq. (34)
Assuming the imaginary part of F(t) = 0 then, ImC.sub.0 (t) =
ImC.sub.2 (t) = 0 and ReC.sub.1 (t) = ReC.sub.3 (t) and ImC.sub.1
(t) = -ImC.sub.3 (t) then:
f(t) = ReC.sub.0 (t) + 2 ReC.sub.1 (t) + ReC.sub.2 (t) Eq. (35)
Equation (35) is implemented by the hardware of FIG. 10 and
consists only of the positive sum of three components. The
amplifier 22 is a non-inverting operational amplifier with four
input terminals each of a + unity gain. The input signal ReC.sub.1
(t) is connected into two input terminals to yield a gain of two.
The output of the inverse continuous transformer 22 is the
reconstituted original input signal f(t).
The continuous Fourier transform mechanism of the present invention
is useful for filtering, signal processing and communications. In
filtering, it may be utilized for lowpass filtering, bandpass
filtering, parallel filtering and chorus filtering (a selected set
of harmonically related frequencies and combinations), specialized
filtering of spectral signatures, and phase lock filtering or phase
discrimination such as that used in space communication, and it is
also useful for complex signal filtering.
The advantage of the continuous Fourier transform apparatus of the
present invention as applied to filtering is that very accurate
frequency selection is obtained there being no practical limit on
the minimum bandwidth. The filtering circuits are inexpensive to
implement in hardware as the hardware comprises merely amplifiers
and in some cases attenuators.
In signal processing, such as in a system described with regard to
FIG. 9, the continuous Fourier transform apparatus of the present
invention is useful for transfer function modification in the
frequency domain. It may also be utilized for spectrum analysis of
continuous data (quasi stationary and non stationary time series
produce deterministic results). It may also be utilized for
serial-to-parallel data conversion and parallel-to-serial data
conversion.
In communications, such as the system described with regard to FIG.
8, the continuous transform mechanism is useful for bandwidth
reduction in the individual communication channels. It may also be
useful for video tape recording utilizing multiple tape heads.
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