Electronic noise attenuation method and apparatus for use in effecting such method

Abstract: A method for electrically attenuating a noise in an area for a sound wave to be propagatable in a three dimensional direction by making up a drive signal from the information on the noise and previously given filter coefficients by use of an adaptive digital filter and then generating an additional sound wave in accordance with the drive signal for cancellation of the noise. In the electric noise attenuation method, there are provided ,in a given region for noise attenuation, first and second error sensor groups for detecting an interference sound wave produced between the noise and additional sound wave, at a sampling time, a filter coefficient is calculated based on the information relating to the first error sensor group, at the next sampling time, another filter coefficient is calculated based on the information relating to the second error sensor group, and these operations are repeatedly executed sequentially for each error sensor to thereby update the filter coefficient of the adaptive digital filter.

Description: BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an electronic noise attenuation method and an apparatus for use in effecting such method and, in particular, to such electronic noise attenuation method which electronically achieves attenuation of a sound wave propagated from a source of noise in an area in which a sound wave can be propagated in a three dimensional direction by generating another sound wave 180° out of phase and the same sound pressure with the propagated sound wave to produce interference between these two sound waves in a given region within the above-mentioned sound propagatable area, and an apparatus for use in effecting such method. 2. Description of the Related Art Conventionally, in an electronic noise attenuation apparatus of the above-mentioned type, in a given area in which a noise is to be attenuated, an additional sound which is 180° out of phase and has the same sound pressure with the noise to be attenuated is generated from a speaker and a drive signal for driving the speaker is made up by an adaptive speaker in accordance with inputs from a sensor microphone to detect the noise and the like as well as in accordance with the output of an error sensor to detect the interference sound between the noise and additional sound in the given noise attenuation area. Referring now to Fig. 4, there is shown a basic structure of the above-mentioned type of conventional electronic noise attenuation apparatus, in which an adaptive digital filter 1 outputs a speaker drive signal y(n) in accordance with an input x(n). In Fig. 4, d(n) designates a desirable response in an error sensor to the input x(n), and e(n) represents an error output to be detected by the error sensor. Also, C designates a transfer function from the sensor to the error sensor. Now, the adaptive digital filter 1 can be realized by a FIR filter having a variable tap weight (filter coefficient) and an adaptive algorithm to control the FIR filter. The adaptive algorithm, in accordance with information of the input x(n) and the error output e(n), adjusts the filter coefficient of the adaptive digital filter so that the energy of the error output e(n) can be the smallest under some evaluation standard. The output y(n) of the adaptive digital filter 1 can be given by convolving the input x(n) and a filter coefficient w i and, therefore, the output y(n) can be expressed by the following equation: and the error output e(n) can be expressed as follows: In the equation (2), the r(n) designates a reference signal which has been filtered and this can be expressed by the following equation: For the purpose of simplification, if the following vector expressions R and W are used, R = [ r (n), r ( n - 1 ), ··· r ( n - I + 1 )] T W = [ w 0 , w 1 ··· w I-1 ] T then the above-mentioned equation (2) can be expressed by the following equation: e (n) = d (n) + R T · W Here, if a mean square error (M S E: mean - square error), [ e(n) 2 ] is found, then J = E [ e (n) 2 ] = E [ e (n) 2 ] + 2 W T [ R T d (n) ] + W T E[ R T R ] W can be obtained from the equation (4). This shows that the MSE is a quadratic function of the filter coefficient. The differential of the quadratic function is a linear function and, therefore, if the differential is assumed to be 0, then a solution having the minimum value J min can be found. Now, in an FX algorithm (Filtered-x LSM algorithm) which is an algorithm in the form of a method of steepest descent, an instantaneous square error e (n) 2 itself is used as the estimator of the MSE J to obtain the estimator ▿ and n of the gradient ▿) of J from the following equation: ▿ n = ∂ e n ∂ W n = 2 e (n) ∂ e n ∂ W n = 2 R T e (n) And, using the above equation ▿ and n , the filter coefficient of the adaptive digital filter can be updated recurrently from the following equation: W n+1 = W n + µ (- ▿ n ) = W n - 2 µ R n T e (n) where µ is a positive scalar serving as a parameter to control the magnitude of an amount of correction in each repetition. The above equation (7) means that the filter coefficients are sequentially updated in an opposite direction (in a direction of the steepest descent of an error curve) to the gradient vector (▿ and n ). If such sequential updating is continued, then at last the MSE reaches the minimum value J min so that the filter coefficient can have the optimum value. While in the above-mentioned FX algorithm the description has been given of a case in which the number of the error output e (n) is one, description will be given below of a case in which a plurality of error sensors are provided and thus the number of the error outputs e (n) are plural so as to be able to extend the given area for noise to be attenuated. Here, as shown in Fig. 5, there are arranged two speakers S 1, S 2 and two error sensors E 1 , E 2 . If the filter coefficients of an adaptive digital filters to output drive signals respectively for driving the speakers S 1 , S 2 are expressed as W 1 , W 2 , respectively and the error outputs of the error sensors E 1 , E 2 are expressed as e = ( e 1 , e 2 ), then the gradient ▿ and n of J can be expressed in the following equation: And, if a control system communication function between the speaker and sensor is expressed as C ℓm , then a reference signal r ℓm (n) made up by convolution of the input x (n) and C ℓm can be expressed by the following equation: where C ℓm , as shown in Fig. 5, is a communication function between an error sensor of the ℓ rank and a speaker of the m rank. And, if the reference signal r ℓm is defined by the following equation, or, r ℓm = [ r ℓm (n), r ℓm ( n - 1 ), ··· r ℓm ( n - j + 1 )] then the above-mentioned equation (8) can be expressed by the following equation: Therefore, in a MEFX algorithm (or Multiple Error Filtered -x Algorithm), the filter coefficients are to be updated in accordance with the following equation; An example of the conventional electronic noise attenuation system incorporating such algorithm is disclosed in PCT-Publication of Japanese Patent Laid-open No. 1-501344 (International Publication No.WO88/02912). As can be understood from comparison between the above mentioned equations (7) and (10), the amount of calculation in the MEFX algorithm to update the filter coefficients of the adaptive digital filter is increased almost in proportion to the number of the error sensors (that is, the number of the error outputs) and, in addition, if the number of the noise sources and speakers (that is, the calculation is required accordingly. Due to the above-mentioned conditions as well as due to the restrictions involved with costs, the capacity of DSP processors and the like, the use of the conventional noise attenuation system has been so far limited to attenuation of periodically occurring noises or pseudo periodical noises. In EP-A-0 333 461 there is disclosed an active acoustic attenuation system for higher order mode non-uniform sound field in a duct. Different sensor groups are used to update different filters, wherein the information from each sensor is not optimally used, since only one filter takes it into account. SUMMARY OF THE INVENTION The present invention aims at eliminating the drawbacks found in the above-mentioned prior art electronic noise attenuation systems. Accordingly, it is an object of the invention to provide an electronic noise attenuation method which is capable of greatly reducing the amount of calculation required for updating the filter coefficients of an adaptive digital filter even when a plurality of error sensors are provided, and an apparatus for use in effecting such method. In order to attain the above object, according to one aspect of the invention, there is provided an electronic noise attenuation method as set out in claim 1. Preferred embodiments of this method are subject matters of claims 2 to 5. According to a second aspect of the invention there is provided an electronic noise attenuation apparatus as set out in claim 6. Preferred embodiments of this apparatus are subject matters of claims 7 to 10. According to the invention, in the filter coefficient updating process for every sampling, a special attention is paid to the instantaneous error output of a certain error sensor. In other words, since all information relating to such error output is known because the information is determined according to the system structure, the filter coefficient of the adaptive digital filter can be calculated based on the error output and the input indicating a noise and in accordance with a given algorithm, and the thus calculated filter coefficient can be used to update the filter coefficient of the adaptive digital filter. Then, in the next sampling, another error sensor is taken up and a similar algorithm is executed to the above case. That is, the error sensors are scanned one by one to thereby update the filter coefficients (which will hereinafter be referred to as "error scanning"). BRIEF DESCRIPTION OF THE DRAWINGS The exact nature of this invention, as well as other objects and advantages thereof, will be readily apparent from consideration of the following specification relating to the accompanying drawings, in which like reference characters designate the same or similar parts throughout the figures thereof and wherein: Fig. 1 is a block diagram of an embodiment of an electronic noise attenuation apparatus according to the invention; Fig. 2 is a graphical representation used to explain the behaviors of filter coefficients to be updated by an ES algorithm according to the invention; Fig. 3 is a view of an example of the arrangements of error sensors to be error scanned; Fig. 4 is a block diagram of a basic structure of an electronic noise attenuation system according to the prior art; and, Fig. 5 is a block diagram of the main portions of an electronic noise attenuation apparatus incorporating therein two speakers and two error sensors. DETAILED DESCRIPTION OF THE INVENTION Detailed description will hereunder be given of the preferred embodiments of an electronic noise attenuation method according to the invention and an apparatus for use in effecting such method with reference to the accompanying drawings. Referring firstly to Fig. 1, there is shown a block diagram of an embodiment of an electronic noise attenuation apparatus according to the present invention, including a single noise source, two error sensors, and two secondary sound wave sources (or speakers). As shown in Fig. 1, the electronic noise attenuation apparatus is mainly composed of a sensor microphone 10, two adaptive digital filters 21, 22, two speakers 31, 32, two error sensors 41, 42 and two controllers 51, 52. The sensor microphone 10 is used to detect a noise from the noise source and output a signal indicating the detected noise through an amplifier 12 and an A/D converter 14 to the adaptive digital filters 21, 22 and the controllers 51, 52. The error sensors 41 and 42 are respectively disposed in a given area for noises to be attenuated, and are respectively used to detect a sound wave produced by interference between the noise from the noise source and the additional sound waves from the speakers 31, 32 and output an error signal indicating the interference sound wave through two amplifiers 43, 44 and two A/D converters to the two controllers 51, 52. The two controllers 51 and 52 are respectively used to calculate filter coefficients W 11 , W 21 , for each sampling in accordance with an error scanning (ES) algorithm and also to update the filter coefficients of the adaptive digital filters 21, 22 by means of the thus calculated filter coefficients W 11 , W 21 , respectively. Also, the controllers 51 and 52 are respectively composed of reference signal operation parts 51A, 51B, 52A, 52B, and ES algorithm execution parts 51C, 52C. The reference signal operation parts 51A, 51B, 52A and 52B are respectively formed of FIR digital filters having filter coefficients C 11 , C 21 , C 12 , and C 22 , respectively indicating communication functions between the speakers 31, 32 and the error sensors 41, 42. Also, the reference signal operation parts 51A, 51B, 52A and 52B respectively make up reference signals R 11 , R 2 1 , R 21 , and R 22 , by means of convolving operations by use of an input X(n) indicating each of the noises to be sequentially sampled at a given cycle and the filter coefficients C 11 , C 21 , C 12 , and C 22 (see the equation (3)), and output these reference signals R 11 , R 21 , R 21 and R 22 to the ES algorithm execution parts 51C and 52C. In the above-mentioned operation, the reference signal operation parts 51A, 52A and 51B, 52B execute their operations alternately for each sampling. Also, in order to identify the coefficient C 11 , the speaker 31 may be previously driven by a pseudo random signal and the output of the FIR digital filter that inputs therein the pseudo random signal is then made to coincide with the error output of error sensor 41. The remaining filter coefficients C 21 , C 12 , and C 22 are previously identified in a similar manner to the filter coefficient C 11 . The ES algorithm execution part 51C is used to calculate the filter coefficient W 11 of the adaptive digital filter 21 according to an adaptive algorithm (that is, ES algorithm) which approximates equivalently to the MEFX algorithm shown by the equation (10) in the adapting process thereof. That is, the ES algorithm execution part 51C executes an ES algorithm shown by the following equation in accordance with the above-mentioned reference signals R 11 , R 21 and error signals e 1 (n), e 2 (n) which are sampled at a given cycle. In other words, at a time (n) of a certain sampling, as shown by the equation (11), the filter coefficient W 1 1 (n+1) is calculated in accordance with the filter coefficient W 11 (n), reference signal R 11 and error signal e 1 (n), and at a time (n+1) of the next sampling, as shown by the equation (12), the filter coefficient W 11 (n+2) is calculated in accordance with the filter coefficient W 11 (n+1), reference signal R 21 and error signal e 2 (n+1). As described above, the ES algorithm pays attention to the error signal of one error sensor for each sampling and updates the corresponding filter coefficient based on a reference signal relating to the error signal and according to the FX algorithm. And, at the next sampling, the ES algorithm then pays attention to the error signal of another error sensor and executes a similar updating processing to the above-mentioned case. Here, in the case of the MEFX algorithm to update the filter coefficient by using a plurality of error signals e 1 (n), e 2 (n) at the same time, the following equation is used: the amount of calculation during one sampling period increases almost in proportion to the number of error sensors when compared with the ES algorithm shown by the above-mentioned equation (11) or (12). Further, in the ES algorithm method, a variable p representing a new time can be defined by the following equation: p = n / 2 , where · represents an integrating operation. As a result of this, the equations (11) and (12) can be expressed approximately as the following equation: It can be understood easily that the above-mentioned equation (14) is a good approximate equation to show the behaviors of the ES algorithm method provided that a step size parameter µ is small enough. The equation (14) is coincident in form with the MEFX that is shown by the equation (13). For this reason, under such a condition that the step size parameter µ is small enough, it should be understood that the equation (14) converges onto the optimum filter coefficient similarly as in the MEFX. Now, the ES algorithm execution part 51C includes operation sections 53, 54, 55 and a selection section 56. The operation section 53 calculates the second term of the right side of the equation (11) in accordance with the reference signal R 11 and the error signal e 1 (n) at a certain time (n), and then outputs the resultant to the operation section 55 through the selection section 56. The operation section 55 includes a memory portion for storing the filter coefficient W 11 . The operation section 55 adds the filter coefficient W 11 stored in the memory section and an output from the selection section 56 to store the resultant sum as a new filter coefficient W 11 (n+1), and then transfers the filter coefficient W 11 (n+1) as the filter coefficient of the adaptive digital filter 21 at the next time (n+1) to thereby update the filter coefficient of the adaptive digital filter 21. Also, the operation section 54, at the next time (n+1), calculates the second term of the right side of the equation (12) in accordance with the R 21 and the error signal e 2 (n+1), and outputs the resultant to the operation section 55 through the selection section 56. Responsive to this, the operation section 55 performs a similar processing to the above-mentioned case to thereby update the filter coefficient of the adaptive digital filter 21. Likewise, the other ES algorithm execution part 52C performs a similar processing to the above-mentioned ES algorithm execution part 51C to thereby update the filter coefficient of the adaptive digital filter 22. The adaptive digital filters 21 and 22 respectively convolve the input X(n) and the filter coefficients W 11 and W 21 to thereby create drive signals, and then output the drive signals through D/A converters 23, 24 and amplifiers 25, 26 to the speakers 31 and 32, respectively. - In this manner, the speakers 31 and 32 can be driven and the additional sound waves that are produced from the speakers 31 and 32 interfere with the noise in a given region, in which the error sensors 41 and 42 are disposed, so as to be able to attenuate the noise. Next, description will be given below of a concept relating to the behaviors of the filter coefficient to be updated by the above-mentioned ES algorithm method. Referring to Fig. 2, there is shown a graphical representation to illustrate a relation between the filter coefficient W (filter degree = first degree). As described before, the MSE can be represented by the quadratic function of the filter coefficient W . Here, in order to update the filter coefficient in accordance with the MEFX algorithm, the filter coefficient may be updated based on the estimate ▿ and n of a local gradient of a curve A indicating J = E [ e 1 2 + e 2 2 ], whereby the filter coefficient is made to approach gradually to the optimum value corresponding to the minimum value J min of the curve A. On the other hand, in order to update the filter coefficient in accordance with the ES algorithm, at a certain time, the filter coefficient may be updated based on the estimate ▿ and n of a local gradient of a curve B indicating J 1 = E [ e 1 2 ] , at the next time, the filter coefficient may be updated based on the estimate ▿ and n of a local gradient of a curve C indicating J 2 = E [ e 2 2 ] , and at the following times the filter coefficients may be sequentially updated based on the estimates ▿ and n to be calculated by switching the curves B and C alternately. If the filter coefficient is updated on in accordance with the ES algorithm, then the MSE reaches the minimum value J min and the filter coefficient becomes the optimum value, similarly as in the case where the filter coefficient is updated based on the curve A. The description has been given heretofore of the illustrated embodiment of an electronic noise attenuation apparatus including one noise source, two error sensors and two speakers. However, the invention is not limited to the number of noise sources and the number of speakers, provided that the number of error sensors is two or more. Also, the number of error sensors to be taken up for each sampling is not limited to one but, for example, as shown in Fig. 3, the error sensors may be divided into a first error sensor group shown by O and a second error sensor group shown by X, and the first and second error sensor groups may be scanned sequentially to thereby update the filter coefficients. Further, for example, assuming that the number of error sensors is 4 (that is, E1, E2, E3 and E4) and a DSP chip is capable of calculating the filter coefficient based on the information as to two error sensors at the same time, according to the ES algorithm of the present invention, the above-mentioned four error sensors can be divided into two groups, that is, (E1, E2) and (E3, E4), and the divided error sensor groups can be scanned alternately to thereby update the filter coefficient. In addition, assuming that the DSP chip is capable of calculating the filter coefficient based on the information as to three error sensors at the same time, according to the ES algorithm of the present invention, the four error sensors can be divided in the following manner and the divided error sensors can be sequentially scanned to thereby update the filter coefficient: 1.) (E1, E2,.E3), (E4) 2.) (E1, E2, E3), (E4, E1, E2), (E3, E4, E1), (E2, E3, E4) 3.) (E1, E2, E3), (E2, E3, E4) The above-mentioned division 1.) illustrates a case when the four error sensors are divided into three error sensors and one error sensor. In this case, it can be understood that the DSP chip does not fulfil 100% of its capability when calculating the filter coefficient based on the information as to the one error sensor. The above-mentioned division 2.) illustrates a case when three error sensors are selected equally out of the four error sensors. In this case, the respective combinations of error sensor groups are sequentially scanned to thereby update the filter coefficient. Four scannings completes one round of the combinations of the error sensors. The division 3.) illustrates a case when three error sensors are selected unequally out of the four error sensors. In other words, the error sensors E2 and E3 are scanned every time, while the error sensors E1 and E4 are scanned every other time. As a result of this, the error sensors E2 and E3 are more weighted than the error sensors E1 and E4. The method of dividing a plurality of error sensors is not limited to the illustrated embodiment but other various methods can be employed according to the number of error sensors, arrangements of the error sensors, and the capabilities of the DSP used. As has been described heretofore, according to the electronic noise attenuation method and apparatus of the present invention, when there are provided a plurality of error sensors, the amount of calculation required for updating the filter coefficient of an adaptive digital filter can be reduced to a great extent. For this reason, even with use of a DSP having the same capability, it is possible to increase the number of noise sources, the number of error sensors and the number of secondary sound wave sources, as well as to expand the processing area.

Claims: An electronic noise attenuation method including the steps of detecting noise information (x) of one or more noise sources in an area for a sound wave to be propagatable in a three-dimensional direction, making up a drive signal for one or more additional sound wave generation means (31, 32) from the noise information (x) detected by adaptive digital filters (21, 22) and previously given filter coefficients (W 11 , W 21 ), and generating, against a sound wave propagated from one noise source, from the one or more additional sound wave generation means (31, 32) an additional sound wave about 180° out of phase and having nearly equal sound pressure with the propagated sound wave, thereby causing the propagated and additional sound waves to interfere with each other so as to attenuate the propagated sound wave in a given region within the propagatable area, said electronic noise attenuation method is characterized by the steps of: (a) arranging in said given region a plurality of error sensors (41, 42) for detecting an intereference sound produced by interference between said propagated sound wave from said noise source and said additional sound wave from said additional sound wave generation means (31, 32); (b) dividing said plurality of error sensors (41, 42) into at least a first error sensor group (41) consisting of one or more error sensors and a second error sensor group (42) consisting of one or more error sensors; (c) when sampling said noise source information and output signals of said plurality of error sensors (41, 42), at a certain sampling time (n), based on only the information (e 1 (n)) relating to said first error sensor group (41) and in accordance with a given algorithm, calculating filter coefficients (W 11 (n+1), W 21 (n+1)) which make it possible for an output signal of said first error sensor group (41) to be the minimum, and updating the filter coefficients (W 11 , W 21 ) of all said adaptive digital filters (21, 22) by said filter coefficients (W 11 (n+1), W 21 (n+1)); (d) at a next sampling time (n+1), based on only the information (e 2 (n+1)) relating to said second error sensor group (42) and in accordance with a given algorithm, calculating filter coefficients (W 11 (n+2), W 21 (n+2)) which make it possible for an output signal of said second error sensor group (42) to be the minimum, and updating the filter coefficients (W 11 , W 21 ) of all said adaptive digital filters (21, 22) by said filter coefficients (W 11 (n+2), W 21 (n+1)); and, repeatedly executing steps (c) and (d) sequentially for each of said divided plurality of error sensors (41, 42) to thereby update the filter coefficients (W 11 , W 21 ) of all said adaptive digital filters (21, 22). The electronic noise attenuation method according to claim 1, wherein, in said adaptive digital filter (21, 22), when a tap number of said adaptive digital filter is I, said noise information at sampling time n, n-1, ..., n-I + 1, are x(n), x(n-1), ..., x(n-I+1), and previously given filter coefficients are W 0 , W 1 , ..., W I-1 , a drive signal y(n) is determined in accordance with the following equations, The electronic noise attentuation method according to claim 2, wherein, when the output signal of said first error sensor (41) at the sampling time (n) is e 1 (n), and the output signal of said second error sensor (42) at a succeeding sampling time (n+1) is e 2 (n+1), the filter coefficients of all said adaptive digital filters (21, 22) can be successively updated in accordance with the following equations, where µ = a step-size parameter, R 1 = a reference signal which has filtered said noise information in an FIR filter having said filter coefficient showing a transfer function from said additional sound wave generation means (31, 32) to the first error sensor (41), and R 2 = a reference signal which has filtered said noise information in the FIR filter having said filter coefficient showing a transfer function from said additional sound wave generation means (31, 32) to the second error sensor (42). The electronic noise attenuation method according to claim 1, wherein each of said plurality of error sensors (41, 42) is obtained by dividing said plurality of error sensors (41, 42) in a manner to be adapted for updating the filter coefficients of all said adaptive digital filters (21, 22) with uniform frequency. The electronic noise attenuation method according to claim 1, wherein each of said plurality of error sensors (41, 42) is obtained by dividing said plurality of error sensors (41, 42) in a manner to be adapted for updating the filter coefficients of all said adaptive digital filters (21, 22) with non-uniform frequency. An electronic noise attenuation apparatus for achieving attenuation of a sound wave propagated from one or more noise sources in a given region within an area for a sound wave to be propagatable in a three dimensional direction by generating an additional sound wave about 180° out of phase and having nearly equal sound pressure with the propagated sound wave to thereby produce sound interference between the propagated and additional sound waves in the given region within the propagatable area, said electronic noise attenuation apparatus characterized by : one or more noise information detection means (10) for detecting the noise information (x) of said one or more noise sources and converting said noise information (x) into an electric signal; one or more additional sound wave generation means (31, 32) for generating an additional sound wave to cancel said propagated sound wave from one noise source in said given region; a plurality of error sensors (41, 42) disposed in said given region for detecting said propagated sound wave from said one noise source and said additional sound wave from said additional sound wave generation means (31, 32) and converting said propagated and additional sound waves into electrical signals; adaptive digital filters (21, 22) for inputting therein an output signal of said noise information detecting means (10) and, based on given filter coefficients (W 11 , W 21 ), making up a drive signal to be given to said additional sound wave generation means (31, 32); and, control means (51, 52) for sampling the output signals from said noise information detection means (10) and from said plurality of error sensors (41, 42), calculating the filter coefficients (W 11 , W 21 ) that make it possible for the output signals of said plurality of error sensors (41, 42) to be the minimum, based on the output signals that are sampled in accordance with a given algorithm in each sampling, and updating the filter coefficients (W 11 , W 21 ) of all said adaptive digital filters (21, 22) by said calculated filter coefficients (W 11 , W 21 ), and, said control means (51, 52) including a program for dividing said plurality of error sensors (41, 42) into at least a first error sensor group (41) consisting of one or more error sensors and a second error sensor group (42) consisting of one or more error sensors, for calculating said filter coefficients (W 11 (n+1), W 21 (n+1)) for all said adaptive filters based on only the information (e 1 (n)) relating to said first error -sensor group (41) at a sampling time (n), for calculating said filter coefficients (W 11 (n+2), W 21 (n+2)) for all said adaptive filters based on only the information (e 2 (n+1)) relating to said second error sensor group (42) at the next sampling time (n+1), and for repeatedly executing each sampling sequentially. The electronic noise attenuation apparatus according to claim 6, wherein, in said adaptive digital filter (21, 22), -when a tap number of said adaptive digital filter is I, said noise information at sampling times n, n-1, ..., n-I + 1, are x(n), x(n-1), ..., x(n-I+1), and previously given filter coefficients are W 0 , W 1 , ..., W I-1 , a drive signal y(n) is determined in accordance with the following equations, The electronic noise attentuation apparatus according to claim 7, wherein, when the output signal of said first error sensor (41) at the sampling time (n) is e 1 (n), and the output signal of said second error sensor (42) at a succeeding sampling time (n+1) ) is e 2 (n+1), the filter coefficients of all said adaptive digital filters (21, 22) can be successively updated in accordance with the following equations, where µ = a step-size parameter, R 1 = a reference signal which has filtered said noise information in an FIR filter having said filter coefficient showing a transfer function from said additional sound wave generation means (31, 32) to the first error sensor (41), and R 2 = a reference signal which has filtered said noise information in the FIR filter having said filter coefficient showing a transfer function from said additional sound wave generation means (31, 32) to the second error sensor (42). The electronic noise attenuation apparatus according to claim 6, wherein a program of said control means adapts each of said plurality of error sensors (41, 42) for updating the filter coefficients of all said adaptive digital filters (21, 22) with uniform frequency. The electronic noise attenuation apparatus according to claim 6, wherein a program of said control means adapts each of said plurality of error sensors (41, 42) for updating the filter coefficients of all said adaptive digital filters (21, 22) with non-uniform frequency.

Inventors: HAMADA HAREO, KINOSHITA AKIO, MIURA TANETOSHI, MIZUNO KEIICHIRO, SATO NORIHARU, TAKAHASHI MINORU, HAMADA, HAREO, KINOSHITA, AKIO, MIURA, TANETOSHI, MIZUNO, KEIICHIRO, SATO, NORIHARU, TAKAHASHI, MINORU
Applicants: BRIDGESTONE CORP, HAMADA HAREO, HITACHI LTD, HITACHI PLANT ENG & CONSTR CO, MIURA TANETOSHI, NISSAN MOTOR, BRIDGESTONE CORPORATION, HAMADA, HAREO, HITACHI PLANT ENGINEERING AND CONSTRUCTION CO., LTD., HITACHI, LTD., MIURA, TANETOSHI, NISSAN MOTOR CO., LTD.
Application year: 1991
Main classification: G10K11
IPC codes: H03H21, G10K11, H04R3, G01H3, H03H17