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Biosystems Research Group II

Biocommunications Research Corporation

G Donald Causey

Daniel Graupe

David L Cohn

Aloysius A Beex

A near minimum order ARMA type recursive filter with guaranteed stability and convergence is provided together with a method for obtaining the parameters of such filter. The amplitude/frequency response of the filter approximates an arbitrarily selected frequency spectrum of amplitude, and the phase response approximates a substantially linear function of frequency with an arbitrarily selected slope because the parameters are identified, off-line, using a minimization process that minimizes an integral error norm. The first step involves performing an inverse discrete Fourier transform of the arbitrarily selected frequency spectrum of amplitude to obtain a truncated sequence of coefficients of a stable, pure moving-average filter model, i.e., the parameters of a non-recursive filter model. The truncated sequence of coefficients, which has N+1 terms, is then convolved with a random sequence to obtain an output sequence associated with the random sequence. A time-domain, convergent parameter identification is then performed, in a manner that minimizes an integral error function norm, to obtain the near minimum order parameters .alpha..sub.i and .beta..sub.j of the model having the desired amplitude- and phase-frequency responses, the parameters satisfying the relationship: ##EQU1## where: .alpha..sub.i is the ith auto-regressive parameter, and .beta..sub.j is the jth moving-average parameter, respectively, of an ARMA-type recursive filter; n and m denote the order of the auto-regressive and the moving-average parts of the ARMA model, respectively; y.sub.k and u.sub.k are associated elements of the kth element of the output sequence and the random sequence, respectively; k is an integer; and v is a shift integer selected to provide the desired slope of the phase response given by 2.pi.(v-N/2).

ARMA filter and method for designing the same

An input signal containing information such as speech or music as well as near-stationary noise is applied in parallel to a noise-analysis circuit and a noise-reduction circuit, each of which comprises a plurality of bandpass filters covering the range of frequencies associated with the information. The absolute value, or a function thereof, of the output of each bandpass filter in the noise-analysis circuit is produced and smoothed. The presence of near-stationary noise in the input signal is determined by examining the nature of the smoothed signal in each band assuming noise has a frequency spectrum which does not vary with time or varies only within a narrow range over a predetermined period of time with respect to the spectral parameters of the information signal. If noise is detected, the noise-analysis circuit identifies spectral parameters of the information and/or noise in each band using the smoothed signal therein. In the preferred embodiment of the invention, the bandpass filters of the noise-reduction circuit have gain elements that are adjusted in accordance with the identified parameters to minimize, under some continuous minimization criterion, the effect of the noise in the input signal thus enhancing intelligibility of the information therein. Minimization can be such that the gain-to-parameter relationships are similar to those in Weiner or Kalman filtering theory with a-priori knowledge of the noise, or of the noise and information, except that in this case, a-priori knowledge of the noise is acquired via identification and is not preassumed.

Method and means for adaptively filtering near-stationary noise from an

An input audio frequency analog signal, for example, speech, which is to be passed through a noisy transmission channel, is scrambled at the sending end by repetitively performing a modulo-v (MOD v) addition of an n-level, m-pulse codeword with an n-level digitized transformation of the input signal under the condition that m and v are integers. The resultant sum signal, after transmission through a noisy channel (which may be an acoustic medium, a conventional telephone link, a conventional CB radio link, etc.), is received at the receiving end and descrambled. Descrambling is achieved by carrying out a Mod v subtraction process involving repetitively subtracting the same codeword from an n-level digitized transformation of the received signal, the subtraction being carried out in synchronism with the addition at the sending end. The resultant difference signal is a representation of the input signal and is relatively insensitive to noise present in the transmission channel.

Method of and means for processing an audio frequency signal to conceal

Processing an input audio-frequency analog signal, for example, speech, which is to be passed through a communication channel, includes performing an n-level digitizing of the input signal, transforming the levels of the digitized signal to other levels using a pre-selected n-bit transformation code, and converting the transformed digitized signal into analog form that is scrambled with respect to the input signal for transmission through the communication channel. At the receiving end of the channel, an n-level digitizing of the transmitted signal is performed, followed by an inverse transformation of the levels of the digitized signal using the inverse of the pre-selected transformation code used on the digitized input signal. The inversely transformed signal is then converted into an analog signal which is representative of the input signal. The communication channel can be an acoustic medium, a telephone line, or a CB radio link. The signal processing means can be realized using microprocessors with fixed or variable programming to change the pre-selected transformation code, or tape or card readers to which a tape or card is applied for the purpose of establishing the pre-selected transformation code.

Method of and means for scrambling and descrambling speech at audio

By identifying and analyzing the properties of the parameters of an input signal that contains speech in the presence of simultaneously occuring near-stationary noise, pauses between speech intervals as well as the termination of such noise can be recognized. When a pause interval containing noise is recognized, the parameters identified during such interval are used to set the parameters of an adaptive filter through which the input signal is passed during subsequent intervals of speech and until the noise terminates. During the time the input signal passes through the filter, the near-stationary noise is filtered out. In response to recognition of the termination of noise, the input signal is caused to by-pass the filter which is then prepared to accept the parameters of noise occuring in a subsequent pause.

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G Donald Causey