The present application relates to a filter and method for an application-specific integrated circuit (ASIC), and more particularly, to a filter and method capable of approximating multiplication operation for the ASIC.
A bi-quadratic (BiQuad) filter is a second-order filter commonly employed in signal processing. In the discrete-time domain, the input/output relation of a BiQuad filter may be expressed as equation (Eq.) 1:
y(n)=b0x(n)+b1x(n−1)+b2x(n−2)−a1y(n−1)−a2y(n−2) Eq. 1
By properly choosing the coefficients [a1, a2, b0, b1, b2], a BiQuad filter may function as a low-pass, high-pass, band-pass, peak, notch, low-shelf or high-shelf filter according to a set of specified parameters such as sampling frequency, center/cutoff frequency fc, Q-factor and gain.
For example, please refer to
However, the above BiQuad filter may require five multiplications, four additions and register several assignment operations. Floating point multiplication, especially 64-bit double precision floating point numbers required for the expressing coefficients in the table 1, is an expensive operation that not only takes significant amount of hardware resources and computation cycles but also consumes significant amount of power.
Therefore, it is necessary to improve the prior art.
It is therefore a primary objective of the present application to provide a filter and method capable of approximating multiplication operation, to improve over disadvantages of the prior art.
An embodiment of the present application discloses a filter. The filter includes at least one first multiplication approximation unit, for approximating at least one first multiplication operation corresponding to at least one first coefficient with at least one first bit-wise shift operation; and at least one second multiplication approximation unit, for approximating at least one second multiplication operation corresponding to at least one second coefficient with a plurality of second bit-wise shift operations and at least one addition operation.
Another embodiment of the present application discloses a method. The method includes approximating at least one first multiplication operation corresponding to at least one first coefficient with at least one first bit-wise shift operation; and approximating at least one second multiplication operation corresponding to at least one second coefficient with a plurality of second bit-wise shift operations and at least one addition operation.
Another embodiment of the present application discloses a filter. The filter includes at least one first multiplication approximation unit, for approximating at least one first multiplication operation corresponding to at least one first coefficient with at least one first bit-wise shift operation.
These and other objectives of the present invention will no doubt become obvious to those of ordinary skill in the art after reading the following detailed description of the preferred embodiment that is illustrated in the various figures and drawings.
Since multiple stages of a BiQuad filter may be used in a system, connecting M stages of the BiQuad filter in cascade results in a 2M-order filter. Under such an arrangement, the input of a stage comes from the output of the previous stage while the output is connected to the input of the next stage.
Please refer to
Under such a situation, each iteration in the processing of the BiQuad filter 20 requires five multiplications, four additions and several register assignment operations. As mentioned in the above, floating point multiplication is an expensive operation that not only takes significant amount of hardware resources and computation cycles but also consumes significant amount of power. Silicon area, computation cycles and power are all precious resource for digital systems, it is therefore highly desirable to have a realization of a BiQuad filter while minimizing the use of floating point multiplier.
When a BiQuad filter is designed in an application-specific integrated circuit (ASIC), arithmetic operations are performed with finite precision. All the variables and constants are represented with finite number of bits. It is inevitable to have errors between the ideal design goal and the actual results produced by a specific digital implementation. Choosing proper precision, or equivalently the number of bits, to represent each of the coefficients existing in the design is critical. The present application aims at the implementations of a BiQuad filter that employ dramatically simplified arithmetic operations and, accordingly, require much less hardware resources while being able to achieve results comparable to that of floating-point arithmetic operations.
Please refer to
In detail, by selecting a proper corner frequency (fC) and a quality factor (Q), multiplication operations by coefficients b0, b1 and b2 become equivalent to bit-wise shift operations as shown in in a table 2 below (fs is a sample rate). Since bit-wise shift operations may be realized by wiring in ASIC design, the resulting implementation of multiplication utilizes no logic gates, takes up no silicon space and consumes no power. In other words, this first step of implementing the BiQuad filter 30 involves choosing suitable combinations of the corner frequency fC and the quality factor Q, and converts the floating point multiplication operations involving the coefficients b0, b1, b2 into no-cost bit-wise rewiring in the ASIC. Then, in the 2nd step of implementing the BiQuad filter 30, the coefficients b0, b1, b2 are finely tuned, such that each of the two floating-point multiplication operations involving coefficients a1, a2 becomes bit-wise shift operations and 2˜3 fixed point addition operations.
Specifically, considering a case where the corner frequency fC≈1439.24 Hz at 48 ksps, the quality factor Q≈0.707 with the following approximations of the coefficients of multiplication operations (converting the coefficients of table 1 with 4th row of the table 2 by approximating each coefficient by a sum of one term (e.g. b0, b1, b2) or more terms (e.g. a1, a2) with each term containing only one ‘1’ in its binary expression):
a1=−1.734863758990959≈−(1.734375)=−(01.101111)b=(0.01)b+(0.000001)b−(010.0)b
a2=0.766113758997616≈0.765625=(0.110001)b=(01.0)b−(0.01)b+(0.000001)b
b0=0.007812500001664≈0.0078125=(0.0000001)b
b1=0.015625000003329≈0.015625=(0.000001)b
b2=0.007812500001664≈0.0078125=(0.0000001)b
where the notation ( )b is the two's-complement binary representation of a number. For example, 1.25=(01.01)b, 0.15625=(0.00101)b, etc.
As shown in
−a1s1(n)=s1(n)×(010.0)b−s1(n)×(0.01)b−s1(n)×(0.000001)b=[s1(n) binary form shifted to the left by 1 bit]−[s1(n) binary form shifted to the right by 2 bits]−[s1(n) binary form shifted to the right by 6 bits]
As a result, three no-cost bit-wise rewiring will address the need of any multiplication operation, and it takes only two integer addition operations to approximate the floating point multiplication operation. By the same token, the multiplication operation of −a2s2(n) in
For those multiplication operations corresponding to the coefficients b0, b1 and b2, since the coefficients b0, b1 and b2 are respectively approximated by a number with only one ‘1’ in their binary expressions, each of the multiplication operations may be obtained by just one no-cost bit-wise shift operation; for instance, b0u(n)≈u(n)×(0.0000001)b=u(n) shifted to the right by 7 bits. Conversions of all six multiplications in a BiQuad filter by shift operations and addition operations are illustrated in
As shown in
Note that the corner frequency fC≈1439.24 Hz is relative to 48 Ksps sample rate. The same set of parameters above may produce the corner frequency fC≈23,028 Hz at 768 Ksps sample rate, the corner frequency fC≈28,785 Hz at 960 Ksps sample rate, the corner frequency fC≈46,056 Hz at 1536 Ksps sample rate, or the corner frequency fC≈92,111.63 Hz at 3072 Ksps sample rate etc. (i.e. with the same fC/fs).
Please refer to
The precisions employed for the variables in the simulations are 16-bit word-length/15-bit fraction-length for the input and output, and 24-bit word-length/17-bit fraction-length for the states and accumulators. In both amplitude and phase responses, the errors between two curves are negligible.
To summarize, the procedures to choose filter coefficients [a1, a2, b0, b1, b2] that may significantly simplify the implementation of a digital BiQuad filter involve
Please refer to
a1=−1.734863758990959≈−(1.75)=−(01.11)b=(0.01)b−(010.0)b
a2=0.766113758997616≈0.875=(0.111)b=(01.0)b−(0.001)b
Additionally, to get the BiQuad filter 60 with unit DC-gain, the coefficients b0, b1 and b2 are scaled by a factor of 4:
b0≈4×0.0078125=(0.00001)b
b1≈4×0.015625=(0.0001)b
b2≈4×0.0078125=(0.00001)b
The multiplication operation corresponding to the coefficient a1 may be replaced by two shift operations and one addition operation, the multiplication operation corresponding to the coefficient a2 may be replaced by one shift operation and one addition operation, and each of the multiplication operations corresponding to the coefficients b0, b1 or b2 may be replaced by 1 shift operation. As shown in
Noticeably, the above embodiments are all for a BiQuad filter. Nevertheless, the approach of using approximate filter coefficients to avoid the use of multipliers and simplify the implementation may be applied to other types of filters or digital signal processors that require multiplication operations. For example, by using the similar rationale, the replacement of coefficient multiplication may be applied to all-poles filter, as shown in left portion of
To sum up, the present application approximates multiplication operations with bit-wise shift operations to save hardware resources.
Those skilled in the art will readily observe that numerous modifications and alterations of the device and method may be made while retaining the teachings of the invention. Accordingly, the above disclosure should be construed as limited only by the metes and bounds of the appended claims.
This application claims the benefits of U.S. Provisional Application No. 63/079,680 filed on Sep. 17, 2020, which are incorporated herein by reference.
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Number | Date | Country | |
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20220085799 A1 | Mar 2022 | US |
Number | Date | Country | |
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63079680 | Sep 2020 | US |