Marantz SA-11S3 Quick reference guide

Introduction

Since the start of the era of digital recording of music, technology

has been faced with the challenge of maximising the accuracy

of reproduction. The initial problem was the small number of bits

available for the conversion of analogue signals into digital. In the

early ‘80s the ﬁrst attempts were made to create more audible

resolution than the bits actually produced. In this way, the ﬁrst

CD player from Philips and Marantz worked with the 14-Bit-D/A-

Converter using a process called noise-shaping and achieved real

precision of 16 bits and four-fold oversampling, and thus played a

leading role.

In recent years, the issue has in fact been reversed, because cur-

rent master and media can easily deal with 24 or even 32-bit and

provide the necessary digital ﬁltering for playing up to 48 bits per

sample. Now the issue centers on reducing the surplus resulting

resolution and the ensuing huge bandwidths by hundreds of

kilohertz as efﬁciently as possible to usable frequencies and the

common resolutions of 16 (CD) to 24 bits. If the excess bits were

shortened to simply remove the excess bits, audible errors would be

created and any higher resolution gained would be irretrievably lost.

In the SA-11S3 Marantz has implemented new algorithms for digital

signal processing developed in-house for the ﬁrst time and the result

is a surprisingly low loss of resolution. For this purpose, Marantz

has utilised new signal processing technology previously exclusively

reserved for high-end, professionally equipped mastering studios.

Solution

To maximise audible resolution, three methods are combined:

Oversampling, Noise Shaping and Dithering.

Through oversampling intermediate samples between 2 original

samples are calculated, thus achieving a multiplication of the

sampling rate. To calculate the intermediate samples with

sufﬁcient accuracy the resolution of the audio data needs to be

increased signiﬁcantly. In our application we found additional

24 bits adequate giving us a total resolution of 48 bits.

The noise shaping offsets digital noise components through clever

ﬁltering from the audible frequency range into the frequency range

beyond 20 kHz, which is no longer perceptible.

With dithering, the desired signal is modulated with noise to

reduce inaccuracies caused through the forcible conversion of reso-

lutions. The type and distribution of the noise determine the quality

of the sonic result. Marantz established the optimal variant through

extensive listening tests and trial series.

As a result of the correct combination of the three methods and the

correct choice of the respective algorithm and its application, more

details than the simple conversion of the original signal could be

perceived, thus signiﬁcantly higher-resolution sound reproduction

could be achieved.

www.marantz.eu Marantz Musical Mastering | SA-11S3 | 1

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Marantz Musical Mastering

SA-11S3

Oversampling

Unlike many procedures used previously, Marantz deploys no rational

numbers for the upsampling of the sampling rate, e.g. 44.1 kHz from

a CD to 96kHz (factor 2.1768 ...), as this is often results in a deteriora-

tion of the “ﬂow” and the “rhythm” of the playback. In its frequency

multiplier Marantz uses exclusively integer factors, and converts the

data with a FIR ﬁlter (ﬁnite impulse response ﬁlter) at either to 352.8

or 384 kilohertz. At the same time, this increases the quantisation

depth up to 48 bits; depending on the corresponding resolution of

the input signal (16 to 24 bits) results in a 2 to 8-fold oversampling.

Noise Shaping

The noise shaping quantiﬁes a mathematical return of rounding

errors back to the beginning of the processing of the audio data.

The effect of this feedback is similar to the “transfer” in manual,

column-by-column addition to or subtraction from two numbers on

the paper. This feedback from the rounding error of the quantiser

is offset against the next digital word (1 sample with up to 48 bits),

added up along with the next random value of the dither and in turn

sent to the quantiser. Over time each rounding error of the voltage

axis (bits) shifts to a correct value on the time axis (sampling

frequency) in this way. The result corresponds more accurately with

the original audio signal with the higher resolution and therefore

sounds better than simply rounding or truncation the signal. The

random element of the dithering signal also prevents the occur-

rence of noise by the feedback of the transfer to the input, as

could occur with the previously mentioned noise shaper procedure

without dithering.

The noise shaper ﬁlter only acts with the LSB (the least signiﬁcant

bit, the “smallest” bit) and returns it to the input of the quantizer

Dithering

Dithering is, put very simply, the signal mixed with noise. In the

reduction from high to low resolution, artifacts which can be

perceived as a distortion occur, as the patterns now appear that do

not belong to an actual music signal.

This can be illustrated through graphic sequencing. The colour

gradient of the diagram, originally 24-bit, was reduced to 4 bits to

illustrate the effect. The problem is transferable between graphics

and audio.

Here is a diagram quantised with 24-bit

colour depth. In this analogy it corre-

sponds with an original, high-resolution

audio signal. It consists of a similar

representation of an analogue image,

with smooth, seamless colours.

If the graphics to illustrate a lower colour

depth are added below, anomalies that

do not match the original (24-bit) appear.

Even artifacts, new image details will be-

come visible in the form of ring patterns

that do not belong to the original image.

The same occurs in the downsampling

of audio signals. When ﬂattening higher

resolutions, interference (distortion)

is created that does not belong to the

original.

If the reduced image is allocated to a

suitable noise, artifacts occurring as a

result of the reduction of the original

low-resolution image disappear almost

completely. With the displaced dither, the

image has a signiﬁcantly greater resem-

blance to the the original high resolution,

despite the lower depth in colour.

Something similar takes place In the

audio processing. With the right dither

displacement, the rounding error is dis-

tributed in a statistically favourable man-

ner, the sound is closer to the original.

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

Original:

24-Bit graphics

Linear scaling:

Reduction to 4 bits.

Quantiser

Noise Shaper Filter

24 Bit

MSB

24 Bit

Dither

48 Bit

Music

Data

24 Bit

LSB

To ensure the generated random signal (noise) remains random

from an acoustic point of view, it may not be repeated at audible

repetition rates. To achieve a minimum repetition rate of 1 second

or higher very long cycle of 180,000 samples are needed. A random

number generator was speciﬁcally developed for this purpose.

When development was in the initial stage there was a noise

signal with a homogeneous uniform distribution of frequency and

amplitude, a so-called ‘white noise’. The graph below shows the

scaled amplitude statistics of this noise signal.

As can be seen the 180.000 samples show very equal probability

between 0 and 1. This means that all amplitudes between 0 and 1

occur equally often.

Listening tests and research have shown that this linear probability

function can be improved further if 2 such noise generators are

used in parallel. Below the scaled amplitude statistics of such a

noise generator.

So far we investigated only the amplitude behaviour of the noise

generator. The frequency behaviour (e.g. spectrum) of our noise

generator looks like this.

It can be seen that all frequencies have about the same amplitude –

thus our noise generator really generates ‘white noise’.

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White noise: a very uniformly distributed random signal.

The resulting noise retains that perfect,yet weighted, random distribution



Again several listing tests have been conducted and ﬁnally the best

sonic performance is achieved with ﬁltered white noise. A high-pass

ﬁlter led to a signiﬁcant improvement in sound. Below the plot of

the spectrum of the ﬁnal dither signal.

This improves the noise spectrum of the resulting

dithered audio signal

Here you can see the distribution of the dither signal, along with its

increasing frequency weighted inﬂuence on the audio spectrum

The weighted noise of the dither signal developed by Marantz is

now stronger at high frequencies than at low frequencies and po-

tential interference components are shifted to the frequency range

that is no longer perceptible, beyond the auditory threshold.

Result

This advanced method of signal processing increases

and maintains the high resolution of both new and old

recordings. The distinct improvement in sound is

manifested in detail in individual instruments, space and

richer tones.

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